Application of computer in agricultural production

0
1
APPLICATIONS OF MS
EXCEL IN AGRICULTURAL
PRODUCTION

1
CHAPTER ONE
EXCEL FUNCTIONS
1. The table belowshowsthe monthlyrelativehumidityof three Local GovernmentAreasof
AnambraState.
A B C D E F
1 Month Awka South Awka North Anaocha
2 January 55.5 45.3 53.7
3 February 48.3 56.7 51.0
4 March 61.0 51.7 60.9
5 April 45.6 48.7 50.0
6 May 56.1 50.9 50.1
7 June 57.5 49.8 60.5
8 July 59.5 59.7 59.0
9 August 47.3 45.9 48.1
10 September 54.8 61.0 45.2
11 October 56.0 50.2 52.7
12 November 48.1 57.6 51.4
13 December 48.1 60.5 52.7
14
15
16
17
Usingrange names:AwkaSouth(B2:B13), AwkaNorth(C2:C13), Anaocha(D2:D13),
i) Calculate in cells B14 to D14 the average monthly relative humidity for Awka South,
Awka North and Anaocha.
ii) Calculate in cells B15 to D15 the maximum relative humidity for Awka South, Awka
North and Anaocha.
iii) Using MATCH function in cells B16 to D17, which months do we have the minimum
relative humidity for Awka South, Awka North and Anaocha.
(Leave your answer in 1 decimal place)
ANSWER TO QUESTION ONE
Step1: To name the range AwkaSouth(B2:B13), highlight cells B2:B13 and then left click and select
Name a Range
Step 2: On the New Name dialogue box, type Awka_South (without giving space) in the Name Box
and then click OK
Step 3: Repeat the process for Awka North and Anaocha
To calculate the average average monthly relative humidity for Awka South, Awka North and
Anaocha:
Step 4: In cell B14 type =AVERAGE(Awka_South) and then press enter key. In cell C14 type
=AVERAGE(Awka_North) and then press enter key. In cell D14 type =AVERAGE(Anaocha) and then
press enter key. (see Figure 1)

2
ANSWER TO QUESTION TWO
To calculate the maximumrelativehumidityforAwkaSouth,AwkaNorthandAnaocha:
Step 1: In cell B15, type =MAX(Awka_South) and then press enter key. In cell C15, type
=MAX(Awka_North) andthenpressenterkey.Incell D15,type =MAX(Anaocha) andthenpressenter
key. (see Figure 1)
ANSWER TO QUESTION THREE
To check the monthwiththe minimumrelative humidity:
Step 1: In cell B16, type =MATCH(Awka_South) and then press the enter key. In cell C16, type
=MATCH(Awka_North) and then press the enter key. In cell D16, type =MATCH(Anaocha) and then
press the enter key.
Step 2: To find the location of the minimum relative humidity for each of them: in cell B17, type
=MATCH(B16,Awka_South,0) andpressthe enterkey. In cell C17, type =MATCH(C16,Awka_North,0)
and press the enter key. In cell D17, type =MATCH(D16,Anaocha,0) and press the enter key.
The answerwill displaythatthe minimumrelative humidity for Awka South is on the fourth month,
which is April; for Awka North is on the first month, which is January; and Anaocha is on the ninth
month which is September (see Figure 1).
Figure 1: Answersto SectionOne Questions
A B C D E F
1 Month Awka South Awka North Anaocha
2 January 55.5 45.3 53.7
3 February 48.3 56.7 51.0
4 March 61.0 51.7 60.9
5 April 45.6 48.7 50.0
6 May 56.1 50.9 50.1
7 June 57.5 49.8 60.5
8 July 59.5 59.7 59.0
9 August 47.3 45.9 48.1
10 September 54.8 61.0 45.2
11 October 56.0 50.2 52.7
12 November 48.1 57.6 51.4
13 December 48.1 60.5 52.7
14 AVERAGE 53.2 53.2 53.0
15 MAXIMUM 61.0 61.0 60.9
16 MINIMUM 45.6 45.3 45.2
17 MATCH 4 1 9
18 MONTH April January September
19
20

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SECTION TWO
Beloware the annual salesfromeggs,annual salesfromchicken and the cost of running the poultry
farm for the year in various farms:
A B C D E F
1
Poultry farms
Annual sales
from eggs
Annual
chicken
Annual
farm cost
2 A 307800 3107500 836490
3 B 305500 2713000 755480
4 C 290000 2871000 830460
5 D 312530 3061000 871975
6 E 315360 3350500 786300
7 F 326600 3230700 789400
8 G 316800 3240000 826005
9 H 299830 2978000 847550
10 I 287300 2691500 959730
11 J 297630 2707900 759365
12 K 327890 3002000 829240
13
14
15
i) Calculate the profit from the poultry farms in cells F2:F12
Check the farms with:
ii) The highest profit
iii) The highest annual farm cost
iv) The highest egg sales
ANSWER TO QUESTION ONE
First of all, to convert the numbers into naira currency, highlight cells A2:D12. Then go to Number
Format on the tool bar which always shows General, select and choose More Number Formats.
Select Currency and on the Symbol section, find naira sign and then click OK (see Figure 2).
To calculate for total sales:
Step 1: Calculate for total sales by typing Total Sales in column E1
Step 2: Type in cell E2 the formula, =SUM(B2:C2) and press the enter key.
Step 3: Drag the answer in cell E2 by click and holding the point at the right edge of the Select Box
through cell E12 to calculate for the total sales of other farms.
To calculate for profit:
Step 1: Type in cell F2, =E2-D2 and press the enter key.
Step 2: Drag the cell from F2 to F12 to calculate for other farms.

4
To check for farms with the highest profit:
Step1: Type incell A13 MaximumProfit, and in cell B13 type =MAX(F2:F12) and press the enter key
Step 2: Type in cell A14 Match, and in cell B14 type =MATCH(B13,F2:F12,0) and press the enter key.
It will display 5, meaning the highest profit made was the fifth farm, E.
To check for the highest annual farm cost:
Step 1: Type in cell A15 Maximum Annual Cost, and in cell B15 type =MAX(D2:D12) and press the
enter key
Step 2: Type in cell A16 =MATCH(B15,D2:D12,0) and press the enter key. It will display 9, meaning
the highest farm cost was incurred in the ninth farm, I.
To check for the highest egg sales:
Step1: Type incell A17 Maximum Egg Sales, and in cell B17 type =MAX(B2:B12) and press the enter
key
Step 2: Type in cell A18 =MATCH(B17,B2:B12,0) and press the enter key. It will display 11, meaning
the highest egg sales were in the eleventh farm, K (see Figure 2).
Figure 2: Answers to Section Two
A B C D E F
1
Poultry farms
Annual sales
from eggs
Annual sales
from chicken
Annual
farm cost Total Sales Profit
2 A ₦ 307,800 ₦ 3,107,500 ₦ 836,490 ₦ 3,415,300 ₦ 2,578,810
3 B ₦ 305,500 ₦ 2,713,000 ₦ 755,480 ₦ 3,018,500 ₦ 2,263,020
4 C ₦ 290,000 ₦ 2,871,000 ₦ 830,460 ₦ 3,161,000 ₦ 2,330,540
5 D ₦ 312,530 ₦ 3,061,000 ₦ 871,975 ₦ 3,373,530 ₦ 2,501,555
6 E ₦ 315,360 ₦ 3,350,500 ₦ 786,300 ₦ 3,665,860 ₦ 2,879,560
7 F ₦ 326,600 ₦ 3,230,700 ₦ 789,400 ₦ 3,557,300 ₦ 2,767,900
8 G ₦ 316,800 ₦ 3,240,000 ₦ 826,005 ₦ 3,556,800 ₦ 2,730,795
9 H ₦ 299,830 ₦ 2,978,000 ₦ 847,550 ₦ 3,277,830 ₦ 2,430,280
10 I ₦ 287,300 ₦ 2,691,500 ₦ 959,730 ₦ 2,978,800 ₦ 2,019,070
11 J ₦ 297,630 ₦ 2,707,900 ₦ 759,365 ₦ 3,005,530 ₦ 2,246,165
12 K ₦ 327,890 ₦ 3,002,000 ₦ 829,240 ₦ 3,329,890 ₦ 2,500,650
13 Maximum profit ₦ 2,879,560
14 Match 5
15 Maximum Annual
Cost ₦ 959,730
16 Match 9
17 Maximum Egg Sales ₦ 327,890
18 Match 11
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SECTION THREE
The data for the number of maize harvested by labourers are given below:
A B C D
1 Labour No. of maize harvested
2 4321 648150
3 5022 753300
4 4032 604800
5 4067 610050
6 4082 612300
7 4023 603450
8 4022 603300
9 4078 611700
10
Using the VLOOKUP function, what will be the likely number of maize harvested given:
i) 5200 labours ii) 4050 labours iii) 4322 labours
Firstof all,the numbershave tobe arranged inascendingordescendingorderforVLOOKUPfunction
to work well.
Step1: To arrange in ascendingorder,select A2:A9 and click on Sort tool bar. Then select B2:B9 and
also click on Sort.
Step 2: Type 5200 in cell A11, 4050 in cell A12, and 4322 in cell A13.
Step 3: Type in cell B11 the formula, =VLOOKUP(A11,A2:B9,2,1) and press the enter key. A11 is
lookupvalue;A2:B9are the lookuparray; 2 is the column number to lookup; and 1 represents TRUE
i.e. not exact match.
Step 4: Drag the answer fromB11 to B13 (see Figure 3).
Figure 3: Answer to Section Three
A B C D
1 Labour No. of maize harvested
2 4321 648150
3 5022 753300
4 4032 604800
5 4067 610050
6 4082 612300
7 4023 603450
8 4022 603300
9 4078 611700
10
11 5200 753300
12 4050 604800
13 4322 648150
14
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SECTION FOUR
The percentage germination of two varieties of beans in different treatments is given below:
A B C D
1 Varieties Treatment % Germination
2 Kafanji Cow dung 42.2
4 Kafanji Poultry manure 30.2
6 Brown beans Cow dung 42.0
7 Brown beans Poultry manure 52.0
10
11
12
Using the average value:
i) Using subtotal command, which of the varieties reported the highest percentage
germination?
ii) Usingstandard deviation,whichof the varietiesreportedhighestvariationingermination?
iii) Using pivot table command which of the treatment reported the highest percentage
germination?
iv) Represent the whole data in a bar chart using pivot chat
First, name the range:
Step 1: To name the range (A2:A9) as Varieties, highlight cells A2:A9 and then left click and select
Name a Range
Step2: Onthe NewName dialogue box, type Varieties (without giving space) in the Name Box and
then click OK
Step 3: Repeat the process for Treatment and % Germination
To find the variety with the highest percentage germination:
Step 1: Highlight cells A1:C9
Step 2: Click on Data and select Subtotal
Step 3: On the Subtotal dialogue box, select Varieties for At each change in
Step 4: On the Use function, select Average
Step 5: On the Add subtotal to, select % Germination
Step 6: Then uncheck Replace current subtotals, and click OK.
The answer will appear thus:
A B C D
6 Kafanji Average 36.3
7 Brown beans Cow dung 42

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8 Brown beans Poultry manure 52
11 Brown beans
Average 50.25
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Therefore, the variety with the highest percentage germination average is Brown beans with
50.25.
To find the variety with the highest variation in germination:
Step 2: Click on Data and select Subtotal
Step 3: On the Subtotal dialogue box, select Varieties for At each change in
Step 4: On the Use function, select StdDev
Step 5: On the Add subtotal to, select % Germination
Step 6: Then uncheck Replace current subtotals, and click OK.
A B C D
6 Kafanji StdDev 6.93
11 Brown beans StdDev 5.56
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Therefore, the variety with the highest variation in germination is Kafanji with 6.93.
To find the treatment with the highest percentage germination using pivot table:
Step 2: Click on Insert and select Pivot Table. When a Create Pivot Table box pops up, click OK
Step 3: On the PivotTable Field List, first check Varieties from Choose fields to add to report to
reflect on the Axis Field, and % Germination to reflect on Values
Step 4: Go to Values and click on the arrow. Select Value Field Settings
Step 5: Then choose Average and click OK.
Row Labels
Average of %
Germination
Brown
beans 50.25
Kafanji 36.3
Grand Total 43.275
Hence, Brown beans variety gave the highest average percentage germination with 50.25.

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To represent the data in bar chart:
Step 2: Click on Insert and select Pivot Chart. When a Create PivotTable with Pivot Chart box pops
up, click OK
Step 3: On the PivotTable Field List, first check Varieties from Choose fields to add to report to
reflect on the Axis Field, and % Germination to reflect on Values.
Step 4: Drag Treatment to Legend Fields.
Step 5: Go to Values and click on the arrow. Select Value Field Settings
Step 6: Then choose Average and click OK.
The table belowshowsthe responses of rural women on challenges affecting their participation in
agriculture:
A B C D E F
1 Inherent challenges SD D UD A SA
2 1 2 3 4 5
3 Lack of capital 42 31 10 28 22
4 High costof inputs 16 28 15 46 28
5 Poor access to market 8 18 12 56 39
6 Lack of processing/storage
facilities
14 25 6 52 36
7 Weak extension servicedelivery 16 22 14 32 49
8 Lack of training programme 43 30 16 28 16
9 Family responsibility 46 38 12 17 20
10 Lack of creditfacilities 8 18 12 56 39
11 Lack of access to land 17 23 8 50 35
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i) Calculate the average response value foreachchallenge
ii) Generate the decisionsforthe challengesusingthe followingrule:
0
10
20
30
40
50
60
Brown beans Kafanji
Cow dung
Poultry manure

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Mean of 3.5 to 5: Great challenge
Mean of 2.5 to 3: Challenge
Mean of lessthan 2.5: Nota challenge
To calculate average (mean) response value:
Step 1: To name the range, highlight cells B2:F2 and then left click and select Name a Range
Step 2: On the New Name dialogue box, type Rank in the Name Box and then click OK
Step 3: Type Mean on cell G1, and on cell G3 type, =SUMPRODUCT(Rank,B3:F3)/133 and press the
Enter key.
Step 4: Drag the answer in cell G3 through G11 to automatically solve for their answers.
To generate the decisionsforthe challenge:
Step1: Type incell H3, =IF(G3>=3.5,”Great challenge”,IF(G3>=2.5,”Challenge”,IF(G3<2.5,”Nota
challenge”)
Step2: Pressthe Enterkeyand drag the answeron cell H3 throughH11 to automaticallysolve the
remainingothers
The answerwill appearthus:
A B C D E F G H
1 Inherent challenges SD D UD A SA Mean Decision
2 1 2 3 4 5
3 Lack of capital 42 31 10 28 22 2.68 Challenge
4 High costof inputs 16 28 15 46 28 3.32 Challenge
5 Poor access to market 8 18 12 56 39 3.75 Great challenge
6 Lack of processing/storage
facilities
14 25 6 52 36 3.53 Great challenge
7 Weak extension service
delivery
16 22 14 32 49 3.57 Great challenge
8 Lack of training programme 43 30 16 28 16 2.58 Challenge
9 Family responsibility 46 38 12 17 20 2.45 Not a challenge
10 Lack of creditfacilities 8 18 12 56 39 3.75 Great challenge
11 Lack of access to land 17 23 8 50 35 3.47 Challenge
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Giventhat:
i. Price that of current price of poultryis₦1,600
ii. Demandof poultryis0.0075*price
iii. Fixedcostis₦2,000
iv. Revenue iscurrentprice*demandforpoultry
v. Profitis Revenue –fixedcost
Calculate the revenue andprofitif price of poultrychangesto₦1,300, ₦1460, ₦1,850 and ₦1,950.
UsingTwo-waydata table:
Type in cell B1,₦1,600
Type in cell B2,=0.0075*B1 andpressthe Enterkey
Type in cell B3,₦2,000
Type in cell B4,=B2*B1 and pressthe Enter key
Type in cell B5,=B4-B3 and pressthe Enter key

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Type Revenue incell C7, and Profitincell D7
Type Price incell A9
List the pricesinascendingorderineachcell fromB9:B13 the following: ₦1,300,₦1,460, ₦1,600,
₦1,850 and ₦1,950
Type in cell C8,=B4 and pressthe Enter key
Type in cell D8, =B5 andpressthe Enter key
HighlightcellsB8:D13 andselect Data andchoose What-IfAnalysis
Choose Data Table,and Data Table box will appear.
Under Columncells,type B1andclickOK.
The answerwill appearthus:
A B C D
1 Current Priceof Poultry ₦ 1,600
2 Demand for poultry (per day) 12
3 Fixed cost(per day) ₦ 2,000
4 Revenue (per day) ₦ 19,200
5 Profit(per day) ₦ 17,200
6
7 Revenue Profit
8 ₦ 19,200 ₦ 17,200
9 Price ₦ 1,300 ₦ 15,600 ₦ 13,600
10 ₦ 1,460 ₦ 17,520 ₦ 15,520
11 ₦ 1,600 ₦ 19,200 ₦ 17,200
12 ₦ 1,850 ₦ 22,200 ₦ 20,200
13 ₦ 1,950 ₦ 23,400 ₦ 21,400
Thismeansthat whenthe price isat ₦1,300 revenue of ₦15,600 and a profitof ₦13,600 are made.
The same isapplicable tothe otherchangingprices.

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CHAPTER TWO
DATA ANALYSIS
ACTIVATING DATA ANALYSISTOOL BAR
UsingExcel to analyse data:
Step1: Clickon Office Button on the topmostleftside of the Windowsview
Step2: Clickon Excel Options
Step3: Clickon Add-ins
Step4: Clickon Go...
Step5: CheckAnalysisToolPak-VBA andExcel Solver
Step6: ThenclickOK.
TWO-SAMPLET TEST (EQUALVARIANCE)
1. The protein contentintwotypesof feedsisgiveninExcel spreadsheetas:
A B C
1 Feed A Feed B
2 0.320 0.322
3 0.332 0.342
4 0.314 0.352
5
Checkif significantdifference existsbetweenthe poultryfeeds.
Solution:
Step1: Go to Data and choose Data Analysis
Step2: Selectt-test:Two-Sample AssumingEqual Variances and clickOK.
Step3: InVariable 1 Range, type A2.A4 and in Variable 2 Range, type B2.B4
Step4: In HypothesizedMeanDifference,type 0.ThenclickOK
The resultwill appearthus:
t-Test: Two-Sample AssumingEqual Variances
Variable 1 Variable 2
Mean 0.322 0.338666667
Variance 8.4E-05 0.000233333
Observations 3 3
Pooled Variance 0.000158667
Hypothesized Mean Difference 0
Df 4
t Stat -1.620509309
P(T<=t) one-tail 0.090219372
t Critical one-tail 2.131846782
P(T<=t) two-tail 0.180438744
t Critical two-tail 2.776445105

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Interpretation:
Variable 1representsFeedA,while Variable 2representsFeedB.
The mean statisticmeansthatthe average proteincontentof the FeedA is 0.322, while that of Feed
B is 0.339.
The calculatedt-statisticvalue of 1.621 is negative becausethe average proteincontentinVariable1
(Feed A) is lower than that of Variable 2 (Feed B).
The tabulated t-value under two-tail test is 2.78. Since the calculated t-statistic value of 1.621 is
lowerthanthe tabulatedt-value,thereisnosignificantdifference in the average protein content of
Feed A and Feed B.
TWO-SAMPLET TEST (UNEQUALVARIANCE)
2. The numberof mangotree samplesfromtwovillagesis giveninExcel spreadsheet below:
A B C D
1 Site Village A Village B
2 1 20 6
3 2 33 10
4 3 44 34
5 4 47 14
6 5 20 40
7 6 15
8
9
Checkif a significantdifference existsinthe numberof mangotreesbetweenthe twovillages.
Solution:
Step2: Selectt-test:Two-Sample AssumingUnequal VariancesandclickOK.
Step3: In Variable 1 Range, type B2.B7 and inVariable 2 Range, type C2.C6
Step4: In HypothesizedMeanDifference,type 0.ThenclickOK

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t-Test: Two-Sample AssumingUnequal Variances
Mean 29.83333333 20.8
Variance 183.7666667 231.2
Observations 6 5
df 8
t Stat 1.03032888
P(T<=t) one-tail 0.166498102
t Critical one-tail 1.859548033
P(T<=t) two-tail 0.332996204
t Critical two-tail 2.306004133
Interpretation:
Variable 1represents Village A,while Variable2representsVillageB.
The mean statistic means that the average number of mango tree in Village A is approximately 30,
while that of Village B is approximately 21.
The t-statistic value of 1.03 is positive because average mango trees in Variable 1 (Village A) are
higher than those in Variable 2 (Village B).
The tabulated t-value is under two-tail test is 2.3. Since the t-test calculated is lower than the
tabulatedvalue, there is no significant difference in the average number of mango trees between
the two villages.
Z-TEST
3. The annual savings membersof marketandproducerfarmscooperative societiesisgiven
below:
A B C D
1 Market cooperative
(₦)
Producer cooperative
(₦)
2 421800 545800
3 439200 492100
4 522000 549100
5 471700 486530
6 544300 541620
7 439600 497050
8 403730 562110
9 466800 592770
10 471500 543660
11 521500 501100
12 416500 482150
13 409850 547700
14 529700 597900
15 440000 506600
16 515000 541700

14
17 450400 556150
18 454700 564700
19 510450 530560
20 512700 517770
21 445640 543800
22 457200 556480
23 527900 504600
24 415940 586300
25 477030 488700
26 517100 500390
27 405500 524350
28 402860 530500
29 481480 532930
30 533300 597330
31 492000 566000
32 415400
33 445100
34 436530
35 503700
36 455500
37 433700
38 491770
39 433700
40 502600
41 500550
i) Checkif a significantdifference existsinthe annual income of the farmers
ii) Whichof the cooperative societieshave higherannual income?
Solution:
Firstperformthe Descriptive statisticstogetthe variance forthe variables:
Step1: Step1: Go to Data and choose Data Analysis
Step2: SelectDescriptive Statistics andclickOK.
Step3: In Input Range, type A2.B41 andcheck Columns underGroupedby
Step4: Check Summary statistics thenclickOK
Column1 Column2
Mean 467898.25 Mean 536281.6667
Standard Error 6704.079039 Standard Error 6164.876281
Median 462000 Median 541660
Mode 433700 Mode #N/A
Standard Deviation 42400.31875 Standard Deviation 33766.41803
Sample Variance 1797787030 Sample Variance 1140170987
Kurtosis - Kurtosis -

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1.266838195 0.787569233
Skewness 0.115106123 Skewness 0.156095435
Range 141440 Range 115750
Minimum 402860 Minimum 482150
Maximum 544300 Maximum 597900
Sum 18715930 Sum 16088450
Count 40 Count 30
Step5: Copyout the sample variance forColumn1and Column2.
Step7: Selectz-test:TwoSample for Meansand clickOK.
Step8: In Variable 1 Range, type A2.A41 and in Variable 2 Range, type B2.B31
Step9: In HypothesizedMeanDifference,type 0.
Step10: Type in the sample variance forColumn1 in Variable 1 Variance (1797787030) andfor
Column2 Variable 2 Variance (1140170987) andclickOK.
z-Test: Two Sample for Means
Mean 467898.25 536281.6667
Known Variance 1797787030 1140170987
Observations 40 30
Z -7.508300022
P(Z<=z) one-tail 2.9976E-14
z Critical one-tail 1.644853627
P(Z<=z) two-tail 5.9952E-14
z Critical two-tail 1.959963985
Interpretation:
Variable 1 or Column 1 represents market cooperative society while Variable 2 or Column 2
represents producer cooperative society
The mean statistics means that the average annual income of market cooperative society is
approximately 467,900 naira while that of producer cooperative society is approximately 536,300
naira
The calculated z-statistics value of 7.51 is negative because Variable 1 average income (market
cooperative society) is lower than Variable 2 average income (producer cooperative society).

16
The tabulatedz-value undertwo-tail test is 1.96. Since the calculated z-statistics is greater than the
tabulatedvalue,there isasignificantdifference inthe annual average income between market and
producer cooperative societies.
Basedon the meanvalue,producer cooperative society has higher annual income when compared
to marketing cooperative society.
DESCRIPTIVE STATISTICS
4. The soil temperature increase withsoil depthinfive differentlocationsisgivenas:
A B C D E F G
1 Soil depth (cm) Sample locations (0C)
2 1 2 3 4 5
3 0-15 30 31 29 30 32
4 15-30 27 29 25 26 28
5 35-40 25 24 20 22 24
6
7
i) Calculate the meanandstandarddeviationof the soil temperature(0
C).
ii) Representyouranswerinmean± standarddeviation.
To analyse:
Step1: SelectData– Data Analysis
Step2: Choose Descriptive StatisticsandclickOK.Descriptive Statisticsdialoguebox willpopup
Step3: UnderInputRange,type B3.F5
Step4: CheckRowsand Summarystatistics,thenclickOK.
A B C D E F G
1 Row1 Row2 Row3 Mean±Std
2
3 Mean 30.4 Mean 27 Mean 23
4
Standard Error 0.509901951
Standard
Error 0.707107
Standard
Error 0.8944272
5 Median 30 Median 27 Median 24
6 Mode 30 Mode #N/A Mode 24
7 Standard
Deviation 1.140175425
Standard
Deviation 1.581139
Standard
Deviation 2
8
Sample Variance 1.3
Sample
Variance 2.5
Sample
Variance 4
9 Kurtosis -0.177514793 Kurtosis -1.2 Kurtosis -0.1875
10 Skewness 0.404796009 Skewness 0 Skewness -0.9375
11 Range 3 Range 4 Range 5
12 Minimum 29 Minimum 25 Minimum 20
13 Maximum 32 Maximum 29 Maximum 25
14 Sum 152 Sum 135 Sum 115
15 Count 5 Count 5 Count 5
16

17
To calculate mean± standard deviation:
Copy out the three meansoncell H2:H4
Copy± signfromWord Symbol on I2:I4
Copyout three standarddeviationsoncell J2:J4
Type in cell K2,=CONCATENATE(H2,I2,J2) andpressthe enterkey
Drag the cell toK3 andK4
G H I J K
1 Mean StdDev Mean±StdDev
2 Row 1 30.4 ± 1.1402 30.4±1.1402
3 Row 2 27 ± 1.5811 27.0±1.5811
4 Row 3 23 ± 2.0000 23.0±2.0000
5
6
ONE-WAYANALYSISOF VARIANCE
5. The growth rate of fishindifferentfeedsisgivenbelow:
A B C D
1 Feeds Growth rate
2 A 0.324
3 A 0.333
4 A 0.341
5 B 0.422
6 B 0.432
7 B 0.412
8 C 0.512
9 C 0.522
10 C 0.513
11 C 0.514
12 D 0.482
13 D 0.477
14 D 0.483
15
i) Is there a significantdifference inthe growthrate of the fishdue to the variousfeeds?
ii) Whichof the feedswill you recommend
Solution:
The data is rearrangedinExcel spreadsheettolookthisway:
A B C D
1 Feed A Feed B Feed C Feed D
2 0.324 0.422 0.512 0.482
3 0.333 0.432 0.522 0.477
4 0.341 0.412 0.513 0.483
5 0.514
6

18
Step2: SelectANOVA:Single Factor andclickOK.
Step3: In Input Range, type A2.D5
Step4: Check Columnand clickOK.
ANOVA: SingleFactor
SUMMARY
Groups Count Sum Average Variance
Column 1 3 0.998 0.332666667 7.23333E-05
Column 2 3 1.266 0.422 0.0001
Column 3 4 2.061 0.51525 2.09167E-05
Column 4 3 1.442 0.480666667 1.03333E-05
ANOVA
Source of Variation SS df MS F P-value F crit
Between Groups 0.062974994 3 0.020991665 441.3275782 4.40512E-10 3.862548358
Within Groups 0.000428083 9 4.75648E-05
Total 0.063403077 12
Interpretation:
From the summary table, Column 1 represents Feed A, Column 2 represents Feed B, Column 3
representsFeedC, andColumn4representsFeedD.The table revealed that average growth rate of
fish is highest in Feed C (0.515 %), and lowest in Feed A (0.333 %).
From the ANOVA table, the calculated F-statistic value is 441.328, while the tabulated F-value is
3.863. Since the calculated F-value of 441.328 is greater than the tabulated value, there is a
significant difference in the average growth rate of fish between the various feed types.
TWO-WAYANALYSISOFVARIANCE
6. The percentage germinationof twovarieties of beansincow dungandpoultrymanure is
givenbelow:
A B C D

19
10
11
12
Checkfor a significantdifference:
i) In the response of the twovarietiesof beans
ii) In the effectof the twomanures
iii) Interaction betweenvarietyandmanure
Solution:
The data is rearrangedinExcel spreadsheetbecause the beansvarietieswere replicated:
A B C D
1 Variety Cowdung Poultry
2 Kafanji 42.2 30.2
3 Kafanji 42.4 30.4
4 BrownBeans 42 52
5 BrownBeans 44 53
6
Step2: SelectANOVA:Two Factor WithReplication and clickOK.
Step3: In Input Range, type A1.C5
Step4: Type 2 in Rows per sample and clickOK.
ANOVA: Two-Factor With Replication
SUMMARY Cowdung Poultry Total
KAFANJI
Count 2 2 4
Sum 84.6 60.6 145.2
Average 42.3 30.3 36.3
Variance 0.02 0.02 48.01333333
BROWN BEANS
Count 2 2 4
Sum 86 105 191
Average 43 52.5 47.75
Variance 2 0.5 30.91666667
TOTAL
Count 4 4
Sum 170.6 165.6
Average 42.65 41.4
Variance 0.836666667 164.4533333

20
ANOVA
Source of Variation SS df MS F P-value F crit
Sample 262.205 1 262.205 412.9212598 3.46288E-05 7.708647421
Columns 3.125 1 3.125 4.921259843 0.090774505 7.708647421
Interaction 231.125 1 231.125 363.976378 4.44725E-05 7.708647421
Within 2.54 4 0.635
Total 498.995 7
Interpretation:
Usingthe average value fromthe summarytable, the percentage germination of Kafanji beans was
higherin cow dung(42.3 %) and lowerinpoultrymanure (30.3 %),while the percentagegermination
of Brown beans was higher in poultry manure (52.5 %) and lower in cow dung (43.0 %). The total
percentage germinationin the two beans varieties was higher in cow dung (42.7 %) than in poultry
manure (41.4 %).
From the ANOVA table,Samplerepresentsbeans varieties and Columns represents treatment. The
calculatedF-value forthe beans varieties is 412.921 and the F-tabulated value is 7.709. Since the F-
calculated value of 412.921 is greater than the F-tabulated, there is a significant difference in the
percentage germination of the two beans varieties.
The calculated F-value for the treatment is 4.921 and the F-tabulated value is 7.709. Since the F-
calculatedvalue of 4.921 islessthanthe F-tabulated,there is no significant difference in the effect
of the treatments between the two beans varieties.
The calculatedF-value forthe interactionis363.976 and the F-tabulatedvalueis7.709. Since the F-
calculatedvalue of 363.976 isgreaterthan the F-tabulatedvalue,there isaninteractionbetween
the beansvarietiesandthe treatments.
SIMPLE DUMMY VARIABLE REGRESSION
Y = a + bx + c where: x = dummyvariable
7. The table belowshowsthe annual income of womenandmenfarmers:
A B C D
1 Gender Annual income (₦) Gender dummy
2 Male 340000 1
3 Male 320000 1
4 Female 360000 0
5 Female 400000 0
6 Male 410000 1
7 Male 480000 1
8 Male 475000 1
9 Male 490500 1

21
10 Female 380000 0
11 Female 325000 0
12 Female 400000 0
13 Male 450000 1
14 Male 480000 1
15 Male 430000 1
16 Female 300000 0
17 Female 310000 0
18 Male 380000 1
i) Generate a dummyvariable forgender
ii) Usingsimple linearregression,findoutif annual income isinfluencedbygender.
Solution:
To performregression:
Step1: Produce the genderdummyvariable byusingIFfunction.Type incell C2the following:
=IF(A2=”Male”,1,0) and pressthe Enterkey
Step2: Drag the resultincell C2 whichwill be 1, throughC18 to produce otherresults.
Step4: SelectRegressionandclickOK
Step5: UnderInput Range Y, type B2.B18, andunderInput Range X type C2.C18
Step6: Check Confidence level at95% andclick OK

22
SUMMARY
OUTPUT
Regression Statistics
MultipleR 0.568722277
R Square 0.323445029
Adjusted R
Square 0.278341364
Observations 17
ANOVA
Df SS MS F
Significance
F
Regression 1 21333178361 21333178361 7.171147409 0.017203994
Residual 15 44622939286 2974862619
Total 16 65956117647
Coefficients
Standard
Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 353571.4286 20615.05213 17.1511295 2.88711E-11 309631.4853 397511.3719 309631.4853 397511.3719
X Variable1 71978.57143 26878.73948 2.677899813 0.017203994 14687.89464 129269.2482 14687.89464 129269.2482

23
INTERPRETATION
Regressionstatistics:
The R square value of 0.323 indicates that the independent variable explained approximately 32%
variability of annual income.
ANOVA statistics:
From the ANOVA table, the calculate F-ratio was 7.171 and has a significant p-value of 0.017
(p<0.05). This indicates that the independent variable has significant effect on changes in annual
income.
Coefficient statistics:
From the table, the coefficient of gender (X variable 1) is 71978.571, which also has a significant p-
value of 0.017. The coefficient of 71978.571 indicates that the male farmers have approximately
71,979 naira more than female farmers.Thisdifference issignificantsince the p-value was less than
0.05.
Hence, it can be concluded that annual income of farmers is determined by gender.
CORRELATION AND MULTIPLE REGRESSIONS
8. The table showsthe demographicdataand economicstatusof XYZ cooperative society:
A B C D E
1
Education Age
Average monthly
income (₦)
Average monthly
savings (₦)
2 Primary 25 45000 5000
3 Secondary 27 50000 15000
4 Tertiary 35 60000 15000
5 Primary 41 55000 6000
6 Tertiary 36 47000 12000
7 Tertiary 29 38000 8000
8 Tertiary 28 42000 10000
9 Primary 44 44000 7000
10 Tertiary 53 70000 8000
11 Secondary 37 28000 6000
12 Secondary 42 47000 11000
13 Primary 28 30000 14000
14 Primary 26 32000 4500
15 Tertiary 43 54000 12000
16 Secondary 48 46000 10000
17
18
19
20
Check:
i) For the correlation betweenall the variables
ii) The influence of education,age andaverage monthlyincome onaverage monthly
savings.

24
Solution:
i) Correlation analysis
Firstof all,code the data for educationusingnestedIFfunction.
Step1: Rightclickon ColumnBand select Insertto insertextracolumnbetweenEducationandAge
Step2: Type inthe newemptycolumnof B1 Education2
Step3: Type inB2 the formula,=IF(A2=”Primary”,1,IF(A2=”Secondary”,2,IF(A2=”Tertiary”,3))) and
pressthe Enter key.Thisassigns1 for Primary,2 for Secondary,and3 for Tertiary.
Thiswill be the newdata sheet:
A B C D E
1
Education Education2 Age
Average monthly
income (₦)
Average monthly
savings (₦)
2 Primary 1 25 45000 5000
3 Secondary 2 27 50000 15000
4 Tertiary 3 35 60000 15000
5 Primary 1 41 55000 6000
6 Tertiary 3 36 47000 12000
7 Tertiary 3 29 38000 8000
8 Tertiary 3 28 42000 10000
9 Primary 1 44 44000 7000
10 Tertiary 3 53 70000 8000
11 Secondary 2 37 28000 6000
12 Secondary 2 42 47000 11000
13 Primary 1 28 30000 14000
14 Primary 1 26 32000 4500
15 Tertiary 3 43 54000 12000
16 Secondary 2 48 46000 10000
Step5: SelectCorrelationandclickOK.
Step6: In Input Range, type B2.E16
Step7: Check Columnand clickOK.
The resultwill appearlike this:
Column
1
Column
2
Column
3
Column
4
Column1 1
Column2 0.218854 1
Column3 0.422022 0.571171 1
Column4 0.431083 -0.04368 0.241854 1

25
Interpretation:
Column 1 represents Education, Column 2 represents Age, Column 3 represents Average monthly
income, and Column 4 represents Average monthly savings.
From the result, there was a correlation between age and average monthly income of the
cooperative society (r≥0.5). However, there were no correlation between education and age,
education and average monthly income, education and average monthly savings, age and average
monthly savings, and average monthly savings and average monthly income of the cooperative
society (r<0.45).
ii) Multiple regressions
Step2: SelectRegressionandclickOK.
Step3: UnderInput Y Range, type E2.E16 because average monthlysavingsisthe dependent
variable
Step4: UnderInput X Range,type B2.D16 because education,age andaverage monthlyincome are
the independentvariables,thenclickOK.

26
The resultwill appearlike this:
SUMMARY OUTPUT
Regression Statistics
MultipleR 0.484382773
R Square 0.234626671
Adjusted R Square 0.025888491
Observations 15
ANOVA
Df SS MS F Significance F
Regression 3 41395965.68 13798655.23 1.124023743 0.381380038
Residual 11 135037367.7 12276124.33
Total 14 176433333.3
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 6839.4 4456.250281 1.534788122 0.153082372 -2968.740733 16647.54073 -2968.740733 16647.54073
X Variable1 1580.230854 1169.334492 1.351393348 0.203707216 -993.4570085 4153.918717 -993.4570085 4153.918717
X Variable2 -103.4622183 129.4817893 -0.799048413 0.441174548 -388.4497149 181.5252784 -388.4497149 181.5252784
X Variable3 0.069765067 0.108463134 0.643214554 0.533264175 -0.168960683 0.308490816 -0.168960683 0.308490816

27
Interpretation:
Regressionstatistics:
The R square value of 0.235 indicates that the independent variable explained approximately 24%
variability of average monthly savings.
ANOVA statistics:
From the ANOVA table, the calculated F-ratio was 1.124 and has a p-value of 0.381. This indicates
that the independent variables have no significant effect on changes in average monthly savings
(p>0.05).
Coefficient statistics:
From the table, X Variable 1 represents Education; X Variable 2 represents Age; and X Variable 3
represents average monthly income.
The coefficient of education (X Variable 1) is 1580.231; the coefficient of age (X Variable 2) has
negative value of 103.4622183; the coefficient of average monthly income (X Variable 3) is
0.069765067, indicating that members of the cooperative society earn approximately 0.1 naira as
monthly income. There was no significant relationship between the average monthly savings and
other dependent variables. Hence, it can be concluded that average education, age and average
monthly income are not determined by average monthly savings.

28
2
APPLICATIONS OF SPSS
IN AGRICULTURAL
PRODUCTION

29
CHAPTER ONE
DESCRIPTIVE AND ONE SAMPLE T-TEST
1. The soil bulkdensity(BD) andexchangeable calcium(CA) isshowninthe table below:
SN BD CA SN BD CA
1. 1.16 3.2 9. 1.16 3.4
2. 1.11 1.8 10. 1.22 5.5
3. 1.14 2.4 11. 1.08 1.4
4. 1.23 5.9 12. 1.09 1.5
5. 1.15 3.0 13. 1.18 3.8
6. 1.12 2.1 14. 1.14 2.6
7. 0.99 0.7 15. 1.11 1.9
8. 1.30 8.2
For each of the samples, determine the mean, median, mode, range and standard deviation
Solution:
UsingSPSS code on differentsheets,the DataView willappearlikethis:
BD CA
1.16 3.2
1.11 1.8
1.14 2.4
1.23 5.9
1.15 3.0
1.12 2.1
0.99 0.7
1.30 8.2
1.16 3.4
1.22 5.5
1.08 1.4
1.09 1.5
1.18 3.8
1.14 2.6
1.11 1.9
Thenthe Variable viewsforbothwill appearlike this:
Name Type Width Decimals Label Values Missing Columns Align Measure Role
BD Numeric 8 2 Bulk density
(g/cm3)
None None 8 Right Unknown Input
CA Numeric 8 2 Exch calcium None None 8 Right Unknown Input
To obtaindata summariesforeachof them, selectthe followingcommands:
Analyze – Descriptive Statistics – Descriptives
Move BD and CA to Variable(s)
Clickon Options
CheckMean, Standarddeviation,Range

30
ClickContinue,OK
The DescriptivesStatisticsfromSPSSOutputare shownbelow:
Descriptive Statistics
N Range Minimum Maximum Mean Std. Deviation
Bulk density (gm/cm3) 15 .31 .99 1.30 1.1453 .07220
Valid N (listwise) 15
Descriptive Statistics
N Range Minimum Maximum Mean Std. Deviation
Exchangeablecalcium 15 7.50 .70 8.20 3.1600 2.00421
Valid N (listwise) 15
ONE-SAMPLET-TEST
This is used to compare the mean of a sample against individual values.
Nine soil scientistsassessedthe soilmoistureof farmlandinUNIZIK.Isthere variationinthe
assessmentof the soil scientist?
Scientist Soil moisture
1 0.3020
2 0.3122
3 0.3420
4 0.3200
5 0.3320
6 0.3320
7 0.330
8 0.3320
9 0.3340
Solution:
Enter the data as above inSPSS:
The Variable viewwill appearlikethis:
Scientist Numeric 8 2 Scientist None None 8 Right Unknown Input
Moisture Numeric 8 2 Soil moisture None None 8 Right Unknown Input
For youto use the One-sample T-test,checkif the datafollow normally.
To do normalitytest,
Go to Analyze – Descriptive Statistics – Explore and move Soil Moisture tothe DependentList.
CheckPlot
ClickPlotandselect NormalityTest with Plots,and uncheck Stem-and-leaf
ClickContinue andOK.

31
The interestfromthe SPSSresultisonlythe table below (forgetthe graph):
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic Df Sig. Statistic df Sig.
Soil moisture .285 9 .034 .884 9 .172
a. LillieforsSignificanceCorrection
Sincethe Sig.of Shapiro-Wilk isgreater than 0.05, data follows normality.Sincethe data follownormality,we
are free to use the One-sample T-test.
To performOne-sample T-test,
Go to Analyze – Compare Means– One-sample Ttest
Move the Soil Moisture toTestVariable,
Type 0 inTest Value,thenclickOK.
The resultwill appearbelow:
Table 1: One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
Soil moisture 9 .3262 .01248 .00416
Table 2: One-Sample Test
Test Value = 0
T Df Sig. (2-tailed) Mean
Difference
95% Confidence Interval of the
Difference
Lower Upper
Soil moisture 78.427 8 .000 .32624 .3167 .3358
Tables 1 and 2 can be arranged into the following:
Parameter Value
Soil moisture 0.3262±0.1248
p-value 0.000
Results are in Mean±Standard Deviation
Interpretation of the Result:
On the average, the nine soil scientists assessed the soil moisture of the farmland in Unizik to be
0.3262±0.1248. This average value differs significantly from individual assessment by the soil
scientists (p<0.05); hence, the assessment vary from one soil scientist to another.
One-sample T-test can be used to compare the mean of a sample against a standard
2. The number of earthworm samples from several farms in UNIZIK is shown below:
Farm No. of earthworm
A 12
B 14
C 20
D 17
E 20
F 12

32
Checkif the number of sampled species of earthworm differ from 18 as common reported in other
studies.
Solution:
Enter the data thiswayin SPSSusing1, 2, 3,4,5,6 for farm A,B, C, D, E and F:
The Variable viewwill appearlikethis:
Farm Numeric 8 2 Farm * None 8 Right Unknown Input
Earthworms Numeric 8 2 No. of
earthworms
None None 8 Right Unknown Input
1, 2, 3,4,5,6 for farm A, B, C, D, E and F
Run normality test as already described.
The interestfromthe SPSSresultisonlythe table below (forgetthe graph):
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
No. of earthworm .203 6 .200* .851 6 .161
*. This is a lower bound of the true significance.
a. LillieforsSignificanceCorrection
Since the Sig.of Shapiro-Wilkisgreaterthan0.05, data followsnormality.Since the datafollow
normality,we are free touse the One-sample T-test.
To performOne-sample T-test,
Go to Analyze – Compare Means– One-sample Ttest
Move the No.of earthwormstoTestVariable,
Type 18 in TestValue,thenclickOK.
The resultwill appearbelow:
Table 3: One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
No. of earthworm 6 15.8333 3.71035 1.51474
Table 4: One-Sample Test
Test Value = 18
T df Sig. (2-tailed) Mean
Difference
95% Confidence Interval of the
Difference
Lower Upper
No. of earthworm -1.430 5 .212 -2.16667 -6.0604 1.7271
Tables 3 and 4 can be arranged into the following:
Parameter Value
Number of earthworms 15.833±3.71035
p-value 0.212

33
Interpretation of the Result:
On the average, the number of earthworms in the six farms was found to be 15.833±3.71035. This
average numberof earthworms does not differ significantly from the commonly reported value of
18 (p>0.05); hence,the numberof earthwormssampledinthe currentstudyisconsistentwiththose
of previous studies.
TWO SAMPLE TESTS
INDEPENDENT-SAMPLES T-TEST
This is used to compare the mean difference between two independent groups.
1. The effect of organic manure on the height (cm) of okra is given below:
Sample Poultry Cowdung
1 11.2 8.4
2 11.7 8.6
3 11.2 8.4
4 12 8
Analyse the datausingIndependentsamplesT-test.
Solution:
UsingSPSS code,the Data Viewwill appearlike this:
Treatment Height
1 11.2
1 11.7
1 11.2
1 12
2 8.4
2 8.6
2 8.4
2 8
1 means poultry, 2 means cow dung
Thenthe Variable viewwill appearlikethis:
Treatment Numeric 8 2 Treatment * None 8 Right Nominal Input
Height Numeric 8 2 Height (cm) None None 8 Right Scale Input
*1, Poultry;2, Cow dung
To obtaindata summaries,selectthe followingcommands:
Analyze – Compare Means – Independent-SamplesTtest
Move Treatmentto GroupingVariablesa-ndHeighttoTest Variable(s),
ThenselectDefine Groups1,2 andclickOK.
The GroupingStatisticsandIndependentSamplesTestfromSPSSOutputare shownbelow:

34
Group Statistics
Treatment N Mean Std. Deviation Std. Error Mean
Height (cm)
Poultry 4 11.5250 .39476 .19738
Cowdung 4 8.3500 .25166 .12583
Independent Samples Test
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t Df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
Height
(cm)
Equal
variances
assumed
2.400 .172 13.564 6 .000 3.17500 .23408 2.60224 3.74776
Equal
variances not
assumed
13.564 5.093 .000 3.17500 .23408 2.57657 3.77343
The data is then arranged for presentation below:
Treatment Okra Height(cm)
Poultry 11.525±0.39476
Cowdung 8.350±0.25166
p-value 0.000
Interpretationof the Result:
Result of the effect of organic manure on the height of okra revealed that poultry manure gave
higher height (11.525±0.39476 cm), while cowdung gave lower height (8.350±0.25166 cm). There
was a significant difference in the height of okra between poultry manure and cow dung (p<0.05).
PAIRED T-TEST
2. Soil temperatures during two growing seasons in northern part of Awka were collected in
pairs: in a clearing (A), and under an adjacent forest canopy (B). Determine if there is a
signficant difference (α = 0.05) in the main soil temperature for the clearing and for the
forest canopy. It can both population are normally distributed.
Sample
Soil temperature (0C) at 50cm depth
A B
1 13.0 9.9
2 13.0 10.0
3 13.1 9.5
4 12.6 9.3
5 10.3 7.5
6 9.5 7.0
7 4.5 3.0
8 9.0 7.0

35
9 11.0 7.5
10 14.0 10.2
11 14.1 10.2
12 14.2 10.4
13 10.4 8.0
14 12.0 7.9
15 13.5 9.3
16 12.5 9.0
17 12.5 9.1
18 14.2 11.0
19 14.4 11.1
20 9.4 7.4
Solution:
Enter the value like thisinSPSS:
SoilTempA SoilTempB
13.0 9.9
13.0 10.0
13.1 9.5
12.6 9.3
10.3 7.5
9.5 7.0
4.5 3.0
9.0 7.0
11.0 7.5
14.0 10.2
14.1 10.2
14.2 10.4
10.4 8.0
12.0 7.9
13.5 9.3
12.5 9.0
12.5 9.1
14.2 11.0
14.4 11.1
9.4 7.4
Go to Analyze - Compare Means- Paired T-test
Move SoilTempAtoVariable 1 and SoilTempBVariable 2
ThenclickOK.
The resultwill be like this:

36
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1
Soil temp. A 11.8600 20 2.45473 .54889
Soil temp. B 8.7150 20 1.87989 .42036
Paired Samples Correlations
N Correlation Sig.
Pair 1 Soil temp. A & Soil temp. B 20 .976 .000
Paired Samples Test
Paired Differences t df Sig. (2-
tailed)Mean Std.
Deviation
Std. Error
Mean
95% Confidence Interval
of the Difference
Lower Upper
Pair 1
Soil temp. A - Soil
temp. B
3.14500 .74231 .16599 2.79759 3.49241 18.947 19 .000
The paired samples statistics table shows that the mean soil temperature in a clearing at 50 cm
depth was higher (11.860±2.45473 0
C) than soil temperature in canopy forest (8.715±1.87989 0
C).
The pairedsamplescorrelationstableshowsthe Pearsonmomentumcorrelationof the temperature
of the twosoil samples.Fromthe table there isapositive correlationbetween soil temperature and
depth. This implies that soil temperature increase with exposure to direct sunlight. The soil
temperature and soil depth were significantly correlated (p<0.05).
The paired-samples T-test compares the mean difference between the soil parameters. From the
table the meandifference betweensoil temperatureof A and B was 3.145. It is positive because the
soil temperature in a clearing is higher than that of canopy forest. The sig (or p-value) is less than
0.05 hence, soil temperature differ by season.
ONE-WAY ANOVA
This is usedto compare the mean difference betweentwoor more groups.
6. The effectof differentsoilsonthe yieldinweight(kg) of yamproduce cultivatedisgiven
below:
Sample Loamy Sandy Clay
1 7.44 5.65 12.55
2 7.83 5.91 12.37
3 7.52 5.94 12.61
4 7.49 6.03 13.14
5 6.88 6.16 12.79

37
Analyse the datausingOne-wayANOVA.
Solution:
UsingSPSS code,the Data Viewwill appearlike this:
Sample Weight
1 7.44
1 7.83
1 7.52
1 7.49
1 6.88
2 5.65
2 5.91
2 5.94
2 6.03
2 6.16
3 12.55
3 12.37
3 12.61
3 13.14
3 12.79
1 means Loamy, 2 means Sandy, 3 means Clay
Then the Variableviewwill appear likethis:
Sample Numeric 8 2 Soil sample * None 8 Right Nominal Input
Weight Numeric 8 2 Weight (kg) None None 8 Right Scale Input
*1, Loamy; 2, Sandy; 3, Clay
To obtaindata summaries,selectthe followingcommands:
Analyze – Compare Means – One-way ANOVA
Move Sample to Factor and WeighttoDependentList.
ThenclickPost-Hocto selectDuncanand Continue.
ClickOptiontoselectDescriptivesandContinue.
The DescriptivesandANOVA fromSPSSOutputare shownbelow:
Descriptives
Weight (kg)
N Mean Std.
Deviation
Std. Error 95% Confidence Interval for
Mean
Minimum Maximum
Lower Bound Upper Bound
Loamy 5 7.4320 .34434 .15399 7.0044 7.8596 6.88 7.83
Sandy 5 5.9380 .18807 .08411 5.7045 6.1715 5.65 6.16
Clay 5 12.6920 .29192 .13055 12.3295 13.0545 12.37 13.14
Total 15 8.6873 3.00971 .77710 7.0206 10.3541 5.65 13.14

38
ANOVA
Weight (kg)
Sum of Squares df Mean Square F Sig.
Between Groups 125.860 2 62.930 789.389 .000
Within Groups .957 12 .080
Total 126.817 14
The data is thenarrangedfor presentationbelow:
Sample Weight (kg)
Loamy 7.432±0.34434
Sandy 5.938±0.18807
Clay 12.692±0.29192
p-value 0.000
Result of the effect of different soils on the yield (kg) of yam revealed that clay soil produced the
highest yield (7.432±0.34434 kg), while sandy soil produced the lowest yield (5.938±0.18807 kg).
There wasa significantdifference inthe weightof yamproducedbetweenthe soilsamples (p<0.05).

39
3
APPLICATIONS OF
MICROSOFT PROJECT
IN AGRICULTURAL
PRODUCTION

40
MS Project – User Manual
Introduction
MS Project has been especially developed for project management and is a useful software
application for planning, tracking and controlling a project.
What can MS Project do for you?
 MS Project is only a tool which supports project managers. It does not execute project
management for you.
 MS Project can do calculations in terms of durations or costs accurately.
 MS Project allows ‘what if scenarios?’,to make changes to the project and see the effects to
those changes before finalising your plan and committing it to work.
 Once your plan is in action, MS Project can track all the information you collect about the
work, duration, costs and resource requirements for your project so that you can make
adjustments in order to keep on target.
 MS Project helps you to create and print various predefined reports and views quickly.
Hovever, which ever project management software package you have in use, the machine cannot do
four things:
 It cannot create the tasks for you
 It cannot create the logical relationships between the tasks
 It does not know the duration of tasks
 It cannot possibly know what resources you have to apply to the tasks
Thus the drawing up of a detailed work plan showing the logic of sequences is an essential part of the
planning process.
NOTE: MS Project also has a very useful Help facility with its own set ofonline tutorials that
you can do at any time.

41
Working with MS Project
Working Area ofthe Screen
The main working area of the screen is split in two main parts: the Entry table on the left and the
Gantt chart [named after the U.S. engineer H. L. Gantt] on the right, separated by a divider bar.
Entry Table
The entry table will contain a listing of every task required by the project and will show calculated
details for each task.
Gantt Chart
The Gantt chart will show bars drawn to represent the duration of each task against a calendar
timescale.
The name of the active view appears on the left edge of the view
Creating a newProject
Before you can put any information into the computer you have to plan the project in some detail:
 Produce a work breakdown structure with a task list
 Produce a time schedule (sequencing and linking of tasks)
 Produce a resource plan (people, material, budget required)
 Assign resources to tasks
Tasks are the basic work units of a project and describe project work in terms of sequence,
duration, and resource requirements.
Setting the project start date and adjusting the project calendar:
Projects can be scheduled from the start date or backwards from the end date.
Set the start/end date as well as the schedule form in the Project Information Pane; to access this
dialog box click on ‘Project’ in the main menu bar and select ‘Project Information …’
For changing the working times of the Standard Calender (Mo – Fri, 8-12 and 13-17) click on ‘Tools’
in the main menu bar and select ‘Change Working Times …’

42
Adjusting the Time Scale Format
In order to change the format of the time scale for the Gantt-Chart select ‘Format’ in the main menu
bar and click on ‘Timescale …’
Enter Task Names and Task Roll Ups
1) If the task table is not already displayed then click ‘Tasks’ on the toolbar
2) Click the cell directly below the Task Name column heading
3) Type in the task name and press ENTER
Each task gets an ID number. Each task has a unique ID number, but it does not necessarily represent
the order in which the tasks occur.
You will notice that the duration defaults to 1 day with a question mark – this indicates that this is an
estimated duration you can change later.
A corresponding task bar of one day’s length appears in the Gantt chart. By default the task start date
is the same as the project start date.
Organising Tasks into Phases:
A summary task,or a roll up, consists of a number of sub-tasks. In the Gantt Chart a summary task
is indicated by the summary task bar and the summary task name appears in bold letters.
To allocate an individual task to a summary task you have to indent the task. You can indent or
outdent a task by selecting the task and clicking on the indent or outdent icon in the tool bar.
Estimating Durations:
The question mark in the duration field indicates that the duration is an estimate. The duration of a
task is the amount of time you expect it will take to complete the task. The durations can range from
minutes to months. But most commonly used are hours, days, and weeks.
Project task durations differ from calendar durations. For instance if you schedule an 8 hours working
day and you have a task that takes 16 hours, you could enter its duration as 2 days to schedule the
work. However, if you schedule the start of the task for Friday 8 am it would not be completed before
Monday 5 pm, because Saturday and Sunday (by default) are scheduled as nonworking time. But of
course it is possible to set the weekend as working time.

43
Milestones:If you enter 0 for the duration of a task the blue bar becomes a black diamond with a date
– this is called a Milestone and denotes an important decision or action point in a project.
After you have entered task durations your project plan should now look similar to the one below:
Linking Tasks
A powerful way of sequencing tasks is to define the predecessor task(s) for each task.
You can select the preceding tasks in the task information pane. In order to display the task
information pane for a specific task, select the task, and either double-click on it or click on the right
mouse button and select Task information …
You will need to go to View > Zoom> Entire Project periodically to keep your project plan in view.
Displaying the project summary task
1) MS Project automatically generates the project summary task but doesn’t display it by
default.
2) Click on Tools in the main menu bar and select Options
3) Select the View pane

44
4) Under ‘Outline options for …’ select the Showproject summary task check box, and then
click OK
5) MS Project displays the project summary task at the top of the Gantt chart view.
Show Outline Number: (WBS Code)
Tools > Options > View > Show outline number
Adjusting Task Relationships:
There are 4 types of task dependencies:
Finish to start: finish date of predecessor determines the start date of the successor
Example:the walls of a house must be erected before you can put on the roof.
Start to start: start date of predecessor determines the start date of the successor.
Example:library research and web research are closely related and can occur simultaneously.
Finish to finish: finish date of the predecessor determines the finish date of the successor
Example:cooking a turkey and potatoes for a dinner. Both dishes need to be ready at the same time,
independently from their individual cooking times.
Start to finish: start date of the predecessor determines the finish date of the successor task. This
relationship is very rarely used.

45
Example:You need a lot of printing paper in your project but don't have room on your office for a
great number of paper boxes, so you only order new printing paper when your supply is running low.
The depletion of paper by current activities triggers an order for more paper.
 Task relationships reflect the sequence in which work should be done.
 By default MS Project uses Start to finish relationships.
 In order to change the task relationship type double click on the task and select the
Predecessor window in the task information pane:
You can also schedule:
 An overlap (called lead time) OR
 A delay (called lag time)
between the finish and start dates of predecessor and successor tasks.
If 2 tasks have a FS-relationship:

46
 Lead time causes the successor task to begin before its predecessor task concludes
 Lag time causes the successor task to begin sometime after its predecessor task concludes.
Task Constraints:
There are 3 categories ofconstraints:
 Flexible constraints
 Semi-flexible constraints
 Inflexible constraints
Setting task constraints:
1) Double-click on a task in order to open the ‘Task Information’ window
2) Select ‘Advanced’
3) You can set a Deadline for this task OR
4) You can choose from a list of constraint types and specify a constraint date.
Flexible task constraints:
Flexible constraints allow tasks to be scheduled without any limitations other than their predecessor
and successor relationships.
No fixed start or end dates are imposed by the constraint types.
Use these constraint types whenever possible!
ASAP (as soon as possible):
This is the default setting in project when scheduling the project from the start date. If you do not
change this constraint, all tasks will occur as soon as they can occur.
ALAP (as late as possible):
Project will schedule all tasks as late as they can occur. This is the default setting in project when
scheduling the project from the end date.
Semi-flexible constraints:
Limit the rescheduling of a task within the date constraints you specify.

47
SNET (start no earlier than):
Use this constraint to ensure that a task will not start before a specific date.
SNLT (start no later than):
Use this constraint to ensure that a task will not start after a specific date.
FNET (finish not earlier than):
Use this constraint to ensure that a task will not finish before a specific date.
FNLT (finish not later than):
Use this constraint to ensure that a task will not finish after a specific date.
Inflexible time constraints:
Completely prevent the rescheduling of a task. Use these constraint types only when absolutely
necessary!
MSO (must start on):
Use this constraint to ensure that a task will start on an exact date.
MFO (must finish on):
Use this constraint to ensure that a task will finish on an exact date.
Use inflexible constraints only ifthe start or the finish date ofa task is fixed by factors beyond
your control.
“Work”, and “Duration” are both measured by time, but “Duration” is different from “Work”. For
this reason, we use a different unit of time for duration.
 Measure work in hours. It is multiplied by the hourly pay rate to calculate labour costs.
 Measure duration in days, or weeks,whatever suits the length of your project.
As an example of why Work and Duration are different, consider these examples:

48
 Quotes are required from suppliers, and although we can send a covering letter with only
3 hours work, allowing the suppliers a 2 week response time might make the total
duration 3 weeks.
Task Types:
There are 3 different task types:
 Fixed Duration
 Fixed Work
 Fixed Units
Fixed Duration
A task takes so long, no, matter how many resources are thrown at it. Paint drying, concrete setting,
machine cycle times, are all examples.
Fixed Work
The amount of work is fixed, but the work will (nearly) half if we double the resources. Getting 2
gardeners to tidy a garden, or 2 painters to emulsion paint a room are good examples.
After a certain point though, the resources start to argue, discuss, and run out of tools or other
resources/materials. Normally there is a limited benefit from adding resources to a task.
Fixed Units
A set number of resources are required to do the task, e.g. student and supervisor in order to discuss
the topic of the diploma thesis.
Project Resources
In a project we need resources – people, equipment, material – to complete the tasks.
With MS Project we can control basically 2 aspects ofresources:
 Availability
 Costs
Availability determines when specific resources can work on tasks and how much work they can.
Costs refer to how much money will be required to pay for those resources.

49
There are 2 types ofresources in MS Project:
 Work resources (people and equipment that do the work)
 Material resources
Examples:
 Individuals identified by name: Claudia Lembach
 Individuals identified by job title / function: supervisor, interviewer
 Groups of people with common skills: electricians, interviewers
 Equipment: Camcorder, batteries
Equipment resources don’t need to be portable: a fixed location (e.g. for a photo shooting, video
editing lab, printing house) can also be considered as equipment.
Entering resources into the Resource Sheet:
1) Click on ‘View’ in the main menu bar and select ‘Resource Sheet’
2) Click in the first cell underneath ‘Resource Name’ and type in the resource name and press
ENTER
3) In the Type field, select either Work or Material.
4) The Max. Units cell represents the maximum capacity of a resource to accomplish a task.
Maximum capacity of 100% this means that 100% of this person’s time is available to work
on a given tasks.
Setting Up Equipment Resources
You can set up people and equipment resources likewise.
Setting up Material Resources
Material resources are consumables that you use up as the project proceeds. For instance material
resources might include batteries, nails, concrete etc.

50
Entering Resource Pay Rates
Tracking and managing cost information allows you to answer questions as:
 What is the expected total cost of the project, based on our task duration and resource
estimates?
 Are we using expensive resources to do work that less expensive resources could do instead?
 How much money will a specific type of resource or task cost during the whole project life
cycle?
 Are we spending money at a rate that we can sustain for the planned duration of the project?
In Resource Sheet,click the ‘Standard Rate’ field to enter pay rates for resources.
Documenting Resources:
1. Double-click on a resource and you will get a screen similar to the one below:
2. Please select the Generals Screen. You can put Email-Address, Specify type of work
3. Please select the Cost Screen. You can see the cost details we specified for our resource.
Adjust the Working Time for the Resources:
A resource calendar controls the working and nonworking times of a resource. By default MS Project
uses the Standard base calendar (Monday to Friday, 8 am to 5 pm)
If all the working times of your resource plan are the same as the Standard base calendar, you do not
need to edit any resource calendars.
However,it is very likely that your resourceswill need exceptions to the working time in the
Standard Calendar, such as:
 A flexible work time schedule
 Vacation time
 Other times when a resource is not available to work on the project, such as time spent on
training or attending a conference
This means, when you change the working time in the Standard Calendar, the changes apply to the
timeframe of the whole project.
Therefore,it is better to apply specific changes to the individual resources rather than to the Standard
Calendar.

51
For changing the individual working times click on ‘Working Times’ in the Resource Information
pane.
Formatting and Printing the Project Plan
Views and reports are the most common ways to see or print a project plan’s data.
The default formatting of the Gantt Chart View works well for onscreen viewing, and printing.
However,it is possible to change the formatting of just about any element on the Gantt-Chart.
3 ways of formatting a Gantt-Chart:
 Format whole categories of Gantt bars in the Bar Styles dialog box,which you can open by
clicking in the Bar Styles command on the Format menu.
 Format whole categories of Gantt bars using the Gantt Chart Wizard, which you can start
by clicking the Gant Chart Wizard command on the Format menu
 Format individual Gantt bars directly by double-clicking on the Gantt bar to get its
formatting options.
Creating a copy of the Gantt Chart
6) Create a copy of the Gantt Chart view so that the formatting changes you make won’t affect
the original Gantt Chart view.
7) On the VIEW menu, click More Views
8) Click the Copy button
9) In the Name Field type ‘Copy of Gantt Chart’ and then click OK
10) In the More Views dialog box, click Apply. Now you have an exact copy of the original
Gantt Chart view. Notice that the view title on the left edge of the view will be modified, too.
Using the Gantt Chart Wizard to format the Gantt bars and milestones in the chart.
1) On the FORMAT menu,click on Gantt Chart Wizard
2) Click Next, click the Other button, and in the drop-down list select for example Style 4
3) Click next and select ‘Resources and Dates’, click Next
4) Select ‘Links’ between tasks,click Next, and then ‘Format it’ and Exit Wizard
5) Select on the File menu, Print Preview and you can see how your project plan will look like
if you print it out.
6) You can likewise format text, Gantt bars, add Resource Initials instead of complete names etc.

52
7) Use Page Setup,on File menu in order to add additional information, e.g. page numbers,
header or footer information etc.
Saving a Project Baseline
A baseline is a collection of important information in your project plan, such as the planned start
dates,finish dates,and the costs of the tasks, resources,and assignments. When you save a baseline,
MS Project takes a snapshot of the existing values and saves it in your project plan for future
comparison.
Saving the project plan as a baseline
1) Make sure you have your project plan saved
2) On the main menu bar click on TOOLS > Tracking > Save Baseline …
3) Save as baseline
4) Project saves the baseline, even though there’s no indication in the Gantt Chart view that
anything has changed.
To viewthe changes caused by saving the baseline:
1) Click on VIEW in the main menu bar, and then select MORE VIEWS
2) Click TASK SHEET,and then APPLY
3) On the main menu bar click on VIEW again and point to TABLE: SUMMARY,and click
Variance
4) The Variance table includes both the scheduled and the baseline start and finish columns,
shown side by side for easy comparison
Assigning Resourcesto Tasks:
Assignment = task + resource
Switch to the Gantt chart view in order to assign resources to tasks.
4 ways of assigning resources to a task
1. Double-click on a task and assign the resources in the resource pane
2. Gantt view, select the task and click on the ‘Assign Resources’ icon in the tool bar
3. Click on ‘Tools’ in the main menu bar and select ‘Assign Resources’

53
4. Gantt view, split window and assign resources in the task form.
The assign resources dialog box appears. In it you can see the resources your can assign or you’ve
already entered.
Assigning resourcesin the split windowview:
Recommended:
Use split windowviewin order to assign resources. MS Projectcan get very confusing when
starting assigning resources to tasks due to task types settings and the so-called effort driven
scheduling.
The Scheduling Formula: Duration, Units, and Work:
MS Project calculates work using the so-called scheduling formula:
Duration x Units = Work
In general, the amount of work will match the duration unless you assign more than one resource to a
task or the one resource you assign is not working full-time.

54
-Example:
Task 4 (Refine Plan) in our ‘Writing a Diploma Thesis’ project has a duration of 3 days. When you
assigned a resource with max. units of 100% to task 4 the scheduling formula looks like this:
24 hours task duration x 100% assignment untis = 24 hours work
If the resource can only work e.g. 70% the work would be 16,8 hours.
On the other hand, if we assign to resources of 100% max. units to this task the works would increase
to 48 hour – the 48 hours is the sum of either resource 24 hours of work. In other words, both
resources will work on the task in parallel.
Effort-driven scheduling method:
By default, MS Project uses a scheduling method called effort-driven scheduling. This means that
the task’s initial work value remains constant, regardless of the number of additional resources you
assign. The most visible effect of effort-driven scheduling is that as you assign additional resources to
a task, that task’s duration decreases or increases.
Project applies effort-driven scheduling only when you assign resources to tasks or remove
resourcesfrom tasks!
The task type determines which of the the three scheduling formula values remains fixed if the other
two values change.
Fixed Units (default task type):
When you change a task’s duration, Project recalculates work. Likewise, if you change a task’s work,
Project recalculates duration.
Fixed Duration:
You can change a task’s units or work value, and Project will recalculate the other value.
Fixed Work:
You can change the units or duration value, and Project will recalculate the other value.
Note that specifying a task as fixed does not mean its duration, units or work are unchangeable. You
can change any value for any task type.

55
Tracking the project’s progress
Tracking means recording project details such as who did what work, when the work was done, and at
what cost. These details are often called ‘actuals’.
Tracking actuals is essential to properly managing a project, as opposed to just planning, a project.
Nevertheless,unless a task has been completed to 100% tracking work in progress is in many cases a
‘best guess’ effort and inherently risky!
Tracking project performance helps you to answer questions such as:
 Are task starting and finishing as planned, and, if not, what will be the impact on the project’s
finishing date?
 Are resources spending more or less time than planned to complete tasks?
 Are higher-than-anticipated task cost driving up the overall cost of the project?
MS Project supports severalways to track progress. The tracking method you choose should depend
on the level of detail or control required by you, your sponsor, and other stakeholders. Tracking the
fine details of the project requires more work from you and possibly from the resources working on
the project.
Levels oftracking:
 Record project work as scheduled. Works best if everything in the projects occurs exactly as
planned.
 Record each task’s percentage of completion, either a precise values or at increments such as
25, 50, 70, 75, or 100
 Record the actualstart, actual finish, actual work, and actual and remaining duration for each
task or assignment.
 Track assignment-level work by time period. This is the most detailed level of tracking. Here
you record actual work values per day, week or another interval.
It is likely, that you might need to apply a combination of these approaches within a single project.
Track a project as scheduled
The simplest approach to tracking a progress on you project is to report that the actual work is
proceeding exactly a planned.

56
E.g. if a certain period of time has elapsed and all of tasks have started and finished as scheduled, you
can quickly record this in the Update Project dialog box
o Switch to Gantt Chart View
o On the Tools Menu,select Tracking and then Update Project
o The Update Project dialog box appears
o Select Update work as complete through and in the date list select the date until the
tasks are completed.
MS Project records the completion percentage for the tasks. It also displays that progress by drawing
progress bars in the Gantt bars for those tasks. Furthermore, check marks appear in the indicator
column for tasks that have been completed.
Entering a Tasks’s Completion Percentage
You can record each task’s percentage of completion, either at precise values or at increments such as
25, 50, 70, 75, or 100
1. Select the task you want to track
2. In the Main Menu bar click on Tracking and then Update Tasks
3. Enter the percentage of completion for the selected task
4. You can also enter the actual duration of a task as well as the actual start and finish dates.
If you change the duration or the start and finish dates project will recalculate the start and
finish times of the related tasks accordingly.
Tracking Actual Work for Tasks and Assignments
The most detailed way of recording actuals is to record the actual work accomplished by the assigned
resources.
1) Switch to the Task Usage View
2) Select the task you want to update in the data spreadsheet and the click on Go to selected task in
the tool bar
3) On the View menu,point to Table: Usage,and then click Work
4) On the Format menu, point to Details,and the click Actual Work
For each task and assignment, Project displays the Work and the Actual Work rows
5) You can enter the actualwork value for the resources in the respective cell

57
4
APPLICATIONS OF
MICROSOFT ACCESS
IN AGRICULTURAL
PRODUCTION

58
1. Microsoft Access 2007 –Overview
a. What isit?
Access 2007 isthe latestandgreatest database developmentapplication
fromMicrosoft.It is one of the many software programsthatmake up MS
Office 2007 whichisavailable onlyforthe WindowsPCoperatingsystem. It
isusedfor creatingbasicletterstomore complex documentslike
newsletters,manuals,forms,andnow blogs
b. Previousversions:
i. WindowsPC:Office 2003 – is compatible with2007 if the updated
compatibilitypackage isdownloadedandinstalled
http://office.microsoft.com/en-us/products/HA101686761033.aspx
ii. Apple Mac: there isno previousversionof Accessforthe Mac
c. It isrecommendedthatduringthe installationof Office 2007 you alsouninstall your
olderversion(s) of Office.Althoughyoucanhave multipleversionsinstalledatthe
same time you will encounterproblems.The mostnoteworthyissueistryingto
opentwoversionsof one program.For instance,if youopenbothWord2003 and
Word 2007, thenrestartyour computeryouwill findthatWordwill notopenright
away.In fact, yourcomputerwill needtoreinstallupontryingtoopenWord2003 or
Word 2007 takinga considerable amountof time
2. Creating and Saving databases
a. What isthis?
A database can be as basic as a contact list or as complex asan entire
organization’sinfrastructure andoperations
b. WhenopeningAccess2007 it automatically promptsyoutochoose how youwantto
start
i. Creating
1. NewBlank Database
a. A wayto start from scratch where the file hasnoexisting
data or objects
2. Templates
a. Eitherfeaturedonlineorlocal,templateshave pre-existing
setupinformationthatwill helpyouwithorganizationand
efficientdatabase development
ii. Choose Blank Database
1. To the right a new columnwill appear
2. Clickthe foldericonunder File Name:
a. In the new window selectMyDocumentsas the locationto
save
i. Thisis the defaultlocationtosave
ii. Thisis the bestchoice to save all of your filesasitis
easyto back up thisfolder
iii. You can alsomake folderswithinthe My
Documents folderforbetterorganization
b. Name the file, sfsu_students.accdb
iii. Saving

59
1. You shouldsave the file asa MicrosoftOffice Access2007 Database
file (.accdb)
a. Thisis notcompatible witholderversionsunlessthe
compatibilitypackage wasinstalledonthe computerthat
triesto openthe file
2. If you wantedtoopenthisfile onan olderversionwithoutusingthe
compatibilitypackage thenyoumustsave the file asan older (.mdb)
file format
3. Clickthe OK button
4. In the columnto the rightunder File Name:click the Create button
iv. Autosave
1. From now on Accesswill automaticallysave yourfilewhenyou
make changes
3. The new Office 2007 interface
a. What isthis?
Knownas a Graphical User Interface (GUI) ituseswindows,icons,pull-down
menus,andthe mouse to make usingthe programeasiertolearnand work
with
b. Title bar
i. File name,format,mode,application
c. QuickAccessToolbar
i. Save,Undo, redo,and the toolbar is completelycustomizable
d. The Office button
i. Similartothe Access 2003 File menu
ii. New,Open,Save,andsoon…
1. Those witharrowshave additional commandsyoucanchoose
iii. Buttonsinbottomright
1. Access Options
2. Exit Access
e. The Office Ribbon
i. Biggestinterface change frompreviousversions
ii. Home,Create, External Data, Database Tools, and soon…
iii. The Ribbon is contextsensitive
1. It may change dependingonwhatyoudo
2. Rightnow you shouldsee asectionnamed Table Tools witha tab
namedDatasheet
a. Thistab is usedwhenworkingona table
iv. Each tab has a numberof groups
1. Whenyouhoveryour mouse pointeroveragroupiteminformation
will typicallyappear
v. In the bottomrightof some grouppanelsyou’ll findalittle diagonal arrow
1. Clickto launcha new window formore optionsandchoiceswithin
that group
vi. The Helpbutton(circle w/a questionmarkinside) islocatedabove andto
the right of the Ribbon
1. Once selectedanew AccessHelp window appears
a. HelpCategories
i. SelectanyTopicunderBrowse Access Helpto find
more helpful Subtopics

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b. HelpSearch
i. Clickinside the textbox,type atopic,andclick
Search
2. You can alsonavigate andfindotherhelpful options(like Home and
Print) on the toolbar locatednear the topof the Help window
vii. Keyboardshortcuts
1. The Alt keyturns on all visibleshortcuts(numbersandletters)
2. Next,pressthe keyboardkeywiththe letterornumberthat
representswhatyouwant
3. Thenyou’ll see thatthe groupswithin thatchoice now have
shortcutsshowingsoyoucan choose the specificoptionwithin
4. The Alt keyturns off all visible shortcutsaswell
viii. Minimize/Maximize the Ribbon
1. Right-clickonanytab or tab group andselectMinimize the Ribbon
4. Views
a. What are these?
Access2007 usesdifferentviewswhenyouare creatingoreditingpartsof
your database.Eachview offersspecificoptionsthatwillhelpyoudesign
and develop
b. Change views
i. On the Ribbon andthe Status Bar (bottomright)
1. On the Ribbon,selectthe Home tab > in the Viewsgroup> select
View(downarrow) > DesignView
2. In the new Save As window, save yourtable usingthe name
students
3. Clickthe OK button
c. On the Ribbon youare now workingwithinthe Designtab
d. Newto Access2007 isthe columnto the left
i. Thiscolumnshowsyourdatabase view,inthatyou can see anyand all
objectstowork with
ii. You can change what youview inthiscolumnbyclickingonthe buttonat
the top of the column
e. Directlybelowthe Ribbonandto the rightof the database/objectsview columnis
your table (students) tab
i. Underneathiswhere youwill definethe fieldsusedinyourtable
ii. Underneaththatis the FieldProperties window where the fieldproperties
are set
5. Create a field
a. What are these?
A table containsdataabout a particularsubject,suchas employeesor
products.Each record ina table containsinformationaboutone item, such
as a particularemployee.A recordismade up of fields, such as name,
addressandtelephone number.A record isalsocommonlycalledarow,and
a fieldisalsocommonlycalledacolumn
b. Create a unique field
i. Newto Accessisthe automaticallygenerated IDfield

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1. Thisfieldisalreadyyourprimary key
a. The primarykeyof a table consistsof one or more fields
that uniquelyidentifyeachrow youstore inthe table.
Often,there isa unique identificationnumber,suchasan ID
number,a serial number,ora code,thatservesas a primary
key.For example,youmighthave aCustomerstable where
each customerhasa unique customerIDnumber.The
customerID fieldisthe primarykeyof the table
b. To assign/removeaprimarykey
i. On the Ribbon > selectthe Designtab > inthe Tools
section> click Primary Key
c. Keepthisfieldasyourprimarykey
2. Under FieldName, name thisfield: 01
a. Thisis yourstudentID # field
3. Under Data Type,choose a type
4. Under Data Type,choose a type*
a. *At the endof thisdocumentisa table that describesthe
data typesavailable forfields
b. The Data Type to choose for thisfieldis Number
6. General fieldproperties
a. What are these?
You can control the appearance of information,preventincorrectentries,
specifydefaultvalues,speedupsearchingandsorting,andcontrol other
appearance or behaviorcharacteristicsbysettingfieldproperties
b. Setupthe fieldproperties
i. In the FieldPropertiesarea,selectthe General tab
ii. For textdata types, Tothe right of FieldSize,type 11
1. Fieldsize isthe maximumamountof charactersthatis neededfor
the fieldforeveryrecord
iii. Clickinside the InputMask textbox andthenselectthe buttonthat appears
to the right
1. An InputMask Wizardwindow will appear
2. Inputmaskscontrol how usersenterdataintoa database.For
example,aninputmaskcanforce usersto entertelephonenumbers
inin the Nigeriaformat
3. The nextsectionof the wizardshouldshow 000-00-0000
a. 0 meansthatthe usermustinputa numberonly
b. You can change thismanuallyif youwant
4. Selectthe Nextbutton
5. How doyou wantto store the data?
a. Selectthe radiobuttonto the leftof, Withthe symbols in
the mask, like this:
7. Selectthe Finishbutton
iv. In the Caption textbox type, StudentID#
1. The Caption you inputwill appearatthe top of the fieldcolumn
whenenteryourdata

62
2. A goodcaptionhelpsyouknow whatyou are supposedtoinput
v. In the Requiredtextbox type, Yes
1. Thisis the optionlike yousee onwebformswhere youhave to
enterthe informationbefore movingontothe nextstep.Same
thinghere where youcannotmove onto the nextrecordunlessthe
correct informationandformatisentered
vi. In the AllowZero Length textbox type, Yes
You can setText or Memo fieldstoazero-lengthstringtoindicate
that the value of a fieldisknownbutthe fieldisempty.Youcanjoin
tablesonzero-lengthstrings,andtwozero-lengthstringswill
compare to be equal.However,for Text,Memo,andHyperlink
fields,youmustsetthe AllowZeroLength propertyto Yesto allow
usersto enterzero-lengthstrings.Other-wise,Accessconvertsa
zero-lengthorall-blankstringtoa Null before storingthe value.If
youalso setthe Requiredpropertyof the Textfieldto Yes,Access
storesa zero-lengthstringif the userenterseither""orblanksin
the field.
Why is it important to differentiate Nulls from zero-length
strings? Here’s an example: Suppose you have a database that
stores the results of a survey about automobile preferences.
For questionnaires on which there is no response to a color-
preference question, it is appropriate to store a Null. You don’t
want to match responses based on an "unknown" response,
and you don’t want to include the row in calculating totals or
averages. On the other hand, some people might have
responded "I don’t care" for a color preference. In this case,
you have a known "nothing" answer, and a zero-length string
is appropriate. You can match all "I don’t care" responses and
include the responses in totals and averages.
vii. In the Indexedtextbox youshouldhave Yes(NoDuplicates)
1. Thiswill speedupsearchesandsorting
2. Thiswill alsocreate a largerfile size andmaybog some databases
down
3. Choose Indexonlyif youfeel youwill searchandsortofteninthis
field
c. Create fields
i. Newfield:
1. FirstName
a. FieldName:fname
b. Date Type:Text
c. FieldProperties:
i. FieldSize:25
ii. Caption:FirstName
iii. Required:YesorNo (yourchoice)
iv. Allow ZeroLength: YesorNo (yourchoice)
v. Indexed:No
2. Last Name

63
a. FieldName:lname
b. Date Type:Text
c. FieldProperties:
i. FieldSize:35
ii. Caption:Last Name
v. Indexed:No
3. StreetAddress
a. FieldName:address
b. Date Type:Text
c. FieldProperties:
i. FieldSize:35
ii. Caption:StreetAddress
v. Indexed:No
7. Lookup wizard
a. What isthis?
A multivaluedlookupcolumn isafieldinatable whose valuesare retrieved
fromanothertable or froma value list.Usingamultivaluedlookupcolumn,
youcan displayalistof choicesina combo box or listbox.The choicescan
be suppliedbyatable or query,or theycan be valuesthatyou enter.
Because the lookupcolumnismultivalued,youcanchoose more thanone
iteminthe list
You can create a multivaluedlookupcolumnmanuallybysettingafield's
Lookupfieldproperties,orautomaticallybycompletingthe LookupWizard.
Wheneverpossible,youshoulduse the LookupWizardtocreate a
multivaluedlookupcolumn.The LookupWizardsimplifiesthe processand
automaticallypopulatesthe appropriatefieldpropertiesandcreatesthe
appropriate table relationships
b. Create a fieldthatusesthe Lookup Wizard
i. Newfield:
1. State
a. FieldName:state
b. Date Type:Lookup Wizard...
i. In the new Lookup Wizardwindow
1. Selectthe radiobuttonto the leftof, I will
type inthe valuesthat I want.
2. Clickthe Nextbutton
3. In the textbox underCol1type the first
value listedbelow,andthentapthe Tab
key,type the nextvalue,andsoon...
a. Anambra
b. Imo

64
c. Enugu
d. Ebonyi
5. Clickthe Finishbutton
c. FieldProperties:
i. FieldSize:35
ii. Caption:State
v. Indexed:No
8. Format, default value, and more input mask
a. What isthis?
A varietyof differentfieldpropertiesthatcanchange the wayyou interact
withyourfieldswhileenteringinyourrecorddata
b. Create a fieldthatusesa specificFormat and a Default Value
i. Newfield:
1. LGA for instantASfor AwkaSouth,AN for AwkaNorthetc
a. FieldName:lga
b. Date Type:Text
c. FieldProperties:
i. FieldSize:2
ii. Format: >
1. Usingthe > symbol meansthatany data
that isenteredinthisfieldwill be
capitalized
iii. Caption:LGA
iv. Default:CA
1. In usingthis,eachrecordwill automatically
have the value LG for LGA
2. Note:the value LG will change to “LG” once
youclick inside anotherpropertytextbox
v. Required:YesorNo (yourchoice)
vi. Allow ZeroLength: YesorNo (yourchoice)
vii. Indexed:No
c. Create a fieldthatusesa the Input Mask
1. The Input Mask shouldalwaysbe usedfor ZipCode
2. ZipCode
a. FieldName:zcode
b. Date Type:Text
c. FieldProperties:
i. FieldSize:11
ii. Clickinside the InputMask textbox andthenselect
the buttonthat appearsto the right
1. If you are promptedtosave the table,then
choose Yes
2. An InputMask Wizardwindow will appear

65
3. SelectZipCode and thenselectthe Next
button
4. The nextsectionof the wizardshouldshow
00000-9999
a. 9 meansthatthe usermay inputa
numberonly
b. You can change thismanuallyif you
want
6. How doyou wantto store the data?
a. Selectthe radiobuttonto the left
of, Withthe symbolsin the mask,
like this:
8. Selectthe Finishbutton
9. Clickinside the Captiontextbox andinthe
Input Mask textbox youshouldnow see
00000-9999;0;_
iii. Caption:ZipCode
iv. Required:YesorNo (yourchoice)
v. Allow ZeroLength: YesorNo (yourchoice)
vi. Indexed:Yes(DuplicatesOK)
9. Validationrule
a. What isthis?
A validationrule limitsorcontrolswhatuserscanenterina table fieldora
control (suchas a textbox) ona form.MicrosoftOffice Access2007 provides
a numberof ways to validate data,andyouoftenuse several of those
techniquestodefineavalidationrule
b. Create a fieldthatusesa ValidationRule
i. Newfield:
1. Gender
a. FieldName:gender
b. Date Type:Text
c. FieldProperties:
i. FieldSize:1
ii. Format: >
iii. Caption:Gender
iv. ValidationRule:
1. Clickinside the textbox andthenclickonthe
Wizardbuttonthat appearsto the right
2. Inputthisrule: F Or M Or B
a. Thismeansone of these three
valuesmustbe entered.Nothing
else will be accepted
v. ValidationText:PleaseenteranF, M, or B only
1. Thismessage will appearwhenthe wrong
value isentered
vi. Required:YesorNo (yourchoice)

66
vii. Allow ZeroLength: YesorNo (yourchoice)
viii. Indexed:No
c. Create a description
i. A descriptionhelpsyoudescribethe fieldandisalsodisplayedinthe status
bar whenyou selectthisfieldonaform(formswill be coveredinthe Access
II class)
ii. Clickinside the textbox tothe rightof the genderfield Data Type and under
the columnheaderDescription
iii. Type:F = female,M= male,B = bi
10. Lookup wizardchallenge
a. What isthis?
A classchallenge tocreate anothermultivaluedlookupcolumn forafield
whose valuesare retrievedfromavalue list.
b. Challenge the classtocreate a fieldthatusesthe Lookup Wizardwiththese 8
college valuesand 1missingvalue
i. Humanities
ii. Business
iii. Science
iv. Creative Arts
v. Education
vi. Ethnic Studies
vii. HSS
viii. BSS
ix. Other
c. Afterthe challenge iscomplete,demonstratehow theyshouldhave createdthe
field
i. Newfield:
1. College
a. FieldName:college
b. Date Type:Lookup Wizard...
i. In the new Lookup Wizardwindow
1. Selectthe radiobuttonto the leftof, I will
type inthe valuesthat I want.
3. In the textbox underCol1type the first
value listedbelow,andthentapthe Tab
key,type the nextvalue,andsoon...
a. Humanities
b. Business
c. Science
d. Creative Arts
e. Education
f. Ethnic Studies
g. HSS
h. BSS
i. Other
5. Clickthe Finishbutton
c. FieldProperties:

67
i. FieldSize:14
ii. Caption:College
v. Indexed:No
d. Limitthe valuesto the list
i. In doingthisonlythe valuesinthe listcanbe
entered,anythingelse will notbe accepted
ii. Selectthe Lookuptab
iii. To the right of Limit To List choose Yes
11. Yes/Nodata type
a. What isthis?
You can setthe Data Type to the Yes/No, whichessentiallyisaTrue/False,
or On/Off predefinedformat
b. Create a fieldthatusesthe Yes/Nodata type
i. Newfield:
1. Financial Aid
a. FieldName:faid
b. Date Type:Yes/No
c. FieldProperties:
i. Caption:Financial Aid
ii. DefaultValue:[blank]
iii. Indexed:No
12. Fields withnumeric value
a. What isthis?
You add a Numberfieldtoa table whenyouneedtostore numericdata,
such as salesfigures.Numbersthathave nonumericvalue shouldbe treated
as a Text data type
b. Create a newfieldthatuseshasnumericvalue
i. Newfield:
1. CreditHours
a. FieldName:chours
b. Date Type:Number
c. FieldProperties:
i. FieldSize:Integer
1. [Byte]:isusedtostore numbers0 through
255. [1 byte]
2. [Integer]:isusedtostore numbers -32,768
through32,767. [2 bytes]
3. [LongInteger]: isusedtostore numbers -
2,147,483,648 through2,147,483,647. [4
bytes]
4. [Single]:real/fractionsrepresentedwith
scientificnotationwithatleast6 digitsof
accuracy. [4 bytes]

68
5. [Double]:real/fractionsrepresentedwith
scientificnotationwithatleast 12 digitsof
accuracy. [8 bytes]
ii. Caption:CreditHours
iii. DefaultValue:[blank]
iv. Required:No
v. Indexed:No
13.Create records
a. What are these?
Each record ina table containsinformationaboutone item, suchasa
particularemployee.A recordismade up of fields, suchas name,address
and telephonenumber.A recordisalsocommonlycalledarow,and a field
isalso commonlycalledacolumn
b. Change view
i. On the Ribbon,(inthe Table Tools section) in the Designtab > in the Views
group> selectView(downarrow) >Datasheet View
ii. Save the table if necessary
c. Create six studentrecords
i. Type in valuesforeachfield forall six records
ii. You can move forwardfromfieldtofieldbyusingthe Tab key onyour
keyboard
iii. You can move backwardby holdingthe Shiftkeydown,and tapingthe Tab
key
iv. You can make selections fromthe dropdownmenusby typingthe firstletter
of the cityin the listandthentapingthe Tab key
v. The space bar will selectthe radiobutton(circle)of yourchoice inthe
Yes/NoFinancial Aid field
d. How manyrecords?
i. In the bottomleftcornerof the datasheetentrywindowyoushouldsee
Record:
1. You will see #of #, whichindicatesthe recordyouare currently
workingwithandthe total numberof records
2. Use the arrow to navigate throughyourrecords
14. Sorting records
a. What isthis?
Data whetheritbe textor numberscan easilybe arrangedorsortedin
ascendingordescendingorder
b. Sort yourrecords
i. To sort alphabeticallybyname move yourmouse pointerinsidethe field
captionLast Name
1. Move the Last Name column
a. Clickonce and letgo
b. Clickinside againbutdon’tletgothistime
c. Move yourmouse pointer(dragthe column) sothatit is
before the fieldcolumn FirstName
d. Let go of your mouse click

69
2. Selectbothname fields
a. Clickinside anycell of anyrecord
b. Clickand holddowninside the LastName fieldcaption
c. Drag your mouse pointerintothe FirstName fieldcaption
(thusselectionbothname columns)
3. Sort the records
a. On the Ribbon,(inthe Table Tools section) in the Datasheet
tab > inthe Sort & Filtergroup > selectAscending( )
15. Create a backup
a. What isthis?
A backupis a copy of the original file.Thisisextremelybeneficial if the
original file iseitherdamagedorlost
b. Close Access
c. Save the table or layoutif necessary
d. OpenyourMy Documents folderforyournew database file
e. Create a backup
i. Move yourmouse pointerintothe file icon
ii. Right-click
iii. From the menuchoose Copy
iv. Move yourmouse pointertoan emptyareainside the folder
v. Right-click
vi. From the menuchoose Paste
vii. Rename the file, sfsu_student_[date].aacdb

70
The followingtable describesthe data typesavailable for fieldsinOffice Access 2007.
Data type Stores Size
Text Alphanumericcharacters
Use fortext,or textand numbersthatare
not usedincalculations(forexample,a
productID).
Up to 255 characters.
Memo Alphanumericcharacters(longerthan255
characters inlength) ortextwithrichtext
formatting.
Use fortextgreaterthan 255 charactersin
length,orfor textthatusesrich text
formatting.Notes,lengthydescriptions,
and paragraphswithformattingsuchas
boldor italicsare goodexamplesof where
youwoulduse a Memo field.
Up to 1 gigabyte of
characters,or 2 gigabytesof
storage (2 bytesper
character),of whichyoucan
display65,535 characters ina
control.
Number Numericvalues(integersorfractional
values).
Use forstoringnumbersto be usedin
calculations,exceptformonetaryvalues
(use the Currencyfordata type for
monetaryvalues).
1, 2, 4, or 8 bytes,or 16 bytes
whenusedforreplicationID.
Date/Time Datesand times.
Use forstoringdate/time values.Note
that eachvalue storedincludesbotha
date componentanda time component.
8 bytes.
Currency Monetaryvalues.
Use forstoringmonetaryvalues
(currency).
8 bytes.
AutoNumber A unique numericvaluethatOffice Access
2007 automaticallyinsertswhenarecord
isadded.
Use forgeneratingunique valuesthatcan
be usedas a primarykey.Note that
4 bytesor 16 byteswhen
usedforreplicationID.

71
AutoNumberfieldscanbe incremented
sequentially,byaspecifiedincrement,or
chosenrandomly.
Yes/No Booleanvalues.
Use forTrue/False fieldsthatcanholdone
of twopossible values:Yes/Noor
True/False,forexample.
1 bit(8 bits= 1 byte).
OLE Object OLE objectsor otherbinarydata.
Use forstoringOLE objectsfromother
MicrosoftWindowsapplications.
Up to 1 gigabyte.
Attachment Pictures,Images,Binaryfiles,Office files.
Thisis the preferreddatatype forstoring
digital imagesandanytype of binaryfile.
For compressedattachments,
2 gigabytes.For
uncompressedattachments,
approximately700k,
dependingonthe degree to
whichthe attachmentcan be
compressed.
Hyperlink Hyperlinks.
Use forstoringhyperlinkstoprovide
single-clickaccess toWebpagesthrougha
URL (UniformResource Locator) orfiles
througha name inUNC (universal naming
convention) format.Youcanalsolinkto
Accessobjectsstoredina database.
Up to 1 gigabyte of
characters,or 2 gigabytesof
storage (2 bytesper
character),of whichyoucan
display65,535 characters ina
control.
Lookup Wizard Notactuallya data type;instead,this
invokesthe LookupWizard.
Use to start the LookupWizardso you can
create a fieldthatusesacombo box to
lookup a value inanothertable,queryor
listof values.
Table or querybased:The size
of the boundcolumn.
Value based:The size of the
Textfieldusedtostore the
value.

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