Loan Project: Buying a House For this assignment, you will analyze a home mortgage loan. 1. Find a description, asking price, and real estate taxes of a house for sale, and decide on a purchase price you would be willing to pay (assuming you have the means). Find a current market interest rate for a 30-year fixed-rate mortgage having a down payment of 20 percent of the purchase price. 2. Compute the down payment, amount financed, and the monthly mortgage payment (showing how to use the appropriate financial formula). 3. Compute the monthly amount of real estate taxes and add to the monthly mortgage payment to get the total monthly amount paid. 4. Suppose that in order to qualify for the loan, the total monthly amount paid cannot exceed 30 percent of monthly income. What is the minimum monthly income needed to qualify for the loan? What is the minimum annual income needed? (Note: This is a simplified minimum income requirement calculation, for the purposes of this project, as it does not take into account other costs such as insurance or other loans or assets currently held.) 5. Construct an amortization table (using spreadsheet software or online resources such as http://www.bankrate.com). 6. Assume that the first payment is made in January of the current year. Find the month and year of the last payment. Find the date of the first month when the amount applied to the principal exceeds the amount of interest paid. How many of the 360 payments have been made at this point? 7. Assuming that the mortgage is held for the full 30 years, compute the total principal paid and the total interest paid. Your report must include · name of project and your name · house's description, asking price, and real estate taxes, the purchase price, and the current market interest rate (include references) · computations and answers for tasks 2, 3, and 4, amortization table for task 5, answers for task 6, and computations and answers for task 7 · conclusion (a paragraph summary describing the results you found to be particularly interesting, and why) Additional details and discussion will be provided in WebTycho conferences. Statistics Project For this assignment, you will implement a project involving statistical procedures. The topic may be something that is related to your work, a hobby, or something you found interesting. If you choose, you may use the example described below. The project report must include · name of project and your name · purpose of project · data (provide the raw data used, and cite the source)—the sample size must be at least 10 · median, sample mean, range, sample variance, and sample standard deviation (show work) · frequency distribution · histogram · percentage of data within one standard deviation of the mean, percentage of data within two standard deviations of the mean, percentage of data within three standard deviations of the mean (include explanation and interpretation --- do your percentages imply that t ...

1. Loan Project: Buying a House
For this assignment, you will analyze a home mortgage loan.
1. Find a description, asking price, and real estate taxes of a
house for sale, and decide on a purchase price you would be
willing to pay (assuming you have the means). Find a current
market interest rate for a 30-year fixed-rate mortgage having a
down payment of 20 percent of the purchase price.
2. Compute the down payment, amount financed, and the
monthly mortgage payment (showing how to use the appropriate
financial formula).
3. Compute the monthly amount of real estate taxes and add to
the monthly mortgage payment to get the total monthly amount
paid.
4. Suppose that in order to qualify for the loan, the total
monthly amount paid cannot exceed 30 percent of monthly
income. What is the minimum monthly income needed to
qualify for the loan? What is the minimum annual income
needed? (Note: This is a simplified minimum income
requirement calculation, for the purposes of this project, as it
does not take into account other costs such as insurance or other
loans or assets currently held.)
5. Construct an amortization table (using spreadsheet software
or online resources such as http://www.bankrate.com).
6. Assume that the first payment is made in January of the
current year. Find the month and year of the last payment. Find
the date of the first month when the amount applied to the
principal exceeds the amount of interest paid. How many of the
360 payments have been made at this point?
7. Assuming that the mortgage is held for the full 30 years,
compute the total principal paid and the total interest paid.
Your report must include
· name of project and your name
· house's description, asking price, and real estate taxes, the
purchase price, and the current market interest rate (include

2. references)
· computations and answers for tasks 2, 3, and 4, amortization
table for task 5, answers for task 6, and computations and
answers for task 7
· conclusion (a paragraph summary describing the results you
found to be particularly interesting, and why)
Additional details and discussion will be provided in WebTycho
conferences.
Statistics Project
For this assignment, you will implement a project involving
statistical procedures. The topic may be something that is
related to your work, a hobby, or something you found
interesting. If you choose, you may use the example described
below.
The project report must include
· name of project and your name
· purpose of project
· data (provide the raw data used, and cite the source)—the
sample size must be at least 10
· median, sample mean, range, sample variance, and sample
standard deviation (show work)
· frequency distribution
· histogram
· percentage of data within one standard deviation of the mean,
percentage of data within two standard deviations of the mean,
percentage of data within three standard deviations of the mean
(include explanation and interpretation --- do your percentages
imply that the histogram is approximately bell-shaped?)
· conclusion (several paragraphs interpreting your statistics and
graphs; relate to the purpose of the project)
If you choose, you may use the following example for your
data.
· Purpose: Compare the amount of sugar in a standard serving

3. size of different brands of cereal. (You may instead choose to
compare the amount of fat, protein, salt, or any other category
in cereal or some other food.)
· Procedure: Go to the grocery store (or your pantry) and pick at
least 10 different brands of cereal. (Instead of choosing a
random sample, you might purposely pick from both the
"healthy" cereal types and the "sugary" ones.)
From the cereal box, record the suggested serving size and the
amount of sugar per serving. The raw data is the serving size
and amount of sugar per serving for each of the 10 boxes of
cereal. Before calculating the statistics on the amount of sugar
in each cereal, be sure you are comparing the same serving size.
If you use a serving size of 50 grams, you must calculate how
much sugar is in 50 grams of each cereal. For example, if the
box states that there are 9 grams of sugar in 43 grams of cereal,
there would be 50 times 9 divided by 43, or 10.5 grams in 50
grams of cereal. The result of this simple calculation (for each
of 10 boxes) is the data you will use in the project statistics and
charts.
Page 1 of 6
Statistics Project
Temperatures in January, 2006 in Purcellville, Virginia
Submitted by Suzanne Sands
Purpose: Analyze temperatures for January, 2006 in my local
region, Purcellville, Virginia.
Most people are interested in the local weather, including me! I

4. focused on the weather in January, 2006. News
reports indicated a much warmer January than usual. I was
interested in compiling descriptive summaries in the
form of charts and numerical measures to get a sense of the
typical temperature for January, 2006, and how the
temperatures have varied over the course of the month. (This
particular project example is an adaptation of similar
project examples I have used in statistics classes I have taught
in the past.)
Data: Random Sample of 30 Temperatures in January, 2006 in
Purcellville, Virginia
Data Collection: An excellent website,
www.weatherunderground.com, provides temperature readings
from
thousands of weather stations. Toward the middle of the screen,
I typed “Purcellville” in the “Location” box and
arrived at the Purcellville forecast. At the bottom of that page,
there are links for personal weather stations. I
clicked on the “Top of Tranquility, Purcellville, VA” link and
arrived at
http://www.wunderground.com/weatherstation/WXDailyHistory.
asp?ID=KVAPURCE1
You can search for weather readings any day you like in the
recent past. This particular weather station

5. recorded 12 temperatures every hour back in 2006, so there
were 12 readings/hr x 24 hours x 31 days = 8,928
temperature readings for January, 2006! I decided to select a
simple random sample of 30 temperatures from
this large collection of data.
I collected 30 temperatures at random times in January, 2006.
(Random sampling is NOT a
requirement for your project. For instance, you could record the
high temperature for each day.)
FYI: Here is how I chose the random sample: Since there are
31 days in January, I generated 30 random numbers
between 1 and 31 (with possible repetition). (You will see
below that many days are repeated.) Next I determined
the sampling times. Since there were 288 temperature readings
each day, I generated 30 random numbers between 1
and 288, representing the reading numbers. Since there were 12
readings per hour, I divided the reading random
number by 12 to get the hour and used the remainder to figure
out which reading to choose during that hour. I
looked up the temperatures for each randomly selected day and
time, and recorded the appropriate temperature.
Count
(January, 2006)

6. Date Time
Temperature
(degrees) Count
(January, 2006)
Date Time
Temperature
(degrees)
1 1 2:41 44.1 16 13 11:55 48.4
2 2 6:35 31.3 17 13 16:01 57.9
3 2 16:21 39.7 18 15 17:35 34.9
4 2 18:11 40.6 19 16 4:55 32.4
5 3 11:45 39.7 20 16 11:11 37.6
6 4 8:05 35.2 21 16 18:35 36.3
7 4 11:55 42.4 22 18 9:01 44.6
8 4 20:35 39.9 23 18 13:45 40.5
9 4 23:52 40.3 24 23 5:41 34.2
10 5 5:21 39.2 25 25 20:31 32.2
11 9 11:31 52.5 26 25 21:31 31.9
12 10 2:45 43.7 27 27 2:11 27.7
13 10 4:21 43.0 28 28 14:35 61.7

7. 14 12 2:31 37.9 29 28 19:21 48.7
15 12 16:55 54.9 30 31 1:01 48.7
Page 2 of 6
Temperature Data, in ascending order:
27.7 31.3 31.9 32.2 32.4 34.2 34.9 35.2 36.3 37.6 37.9 39.2 39.7
39.7 39.9
40.3 40.5 40.6 42.4 43.0 43.7 44.1 44.6 48.4 48.7 48.7 52.5 54.9
57.9 61.7
Notes: To construct a frequency distribution, typically we need
to group the data into about four to eight intervals. In
looking over the sorted data, ranging from 27.7 to 61.7, it seems
reasonable to use intervals of width 5 or 10 degrees.
Frequency Distribution:

8. Grouped in intervals of 10 degrees
Grouped in intervals of 5 degrees
REMARKS: Both tables show that the temperatures are
principally clustered in the 30’s and 40’s. Which
table is better? It’s really a toss-up; either one is fine. It’s not
necessary to make more than one table. I am
showing two tables, just for illustration purposes.
If a table has very low frequencies for all of the intervals (say a
frequency of 1-2 for each interval), or if
there are more than 10 intervals, that would be an indication

9. that the interval width is too small. For
example, if each interval consisted of just one degree, then the
frequency table for this temperature data
would have over 30 rows and that table would not be very
informative, in terms of helping to see where
the data are clustered.
30 Random Temperatures in January, 2006,
Purcellville, VA
Temperature
(degrees) Frequency
Relative
Frequency
19.95 - 29.95 1 .033
29.95 - 39.95 14 .467
39.95 - 49.95 11 .367
49.95 - 59.95 3 .100
59.95 - 69.95 1 .033
Total 30 1.000
30 Random Temperatures in January, 2006,
Purcellville, VA
Temperature

10. (degrees) Frequency
Relative
Frequency
24.95 - 29.95 1 .033
29.95 - 34.95 6 .200
34.95 - 39.95 8 .267
39.95 - 44.95 8 .267
44.95 - 49.95 3 .100
49.95 - 54.95 2 .067
54.95 - 59.95 1 .033
59.95 - 64.95 1 .033
Total 30 1.00
Page 3 of 6
Histogram
The histogram is a visual representation of the frequency
distribution on the previous page, with the
temperatures grouped in intervals of 5 degrees.

11. The majority of temperatures fall between 34.95 and 44.95
degrees.
The histogram was generated with spreadsheet software. Your
histogram does not have to be fancy. It can be hand-
drawn or typed in plain text form. It is important that the scales
and the labeling are clear and accurate.
Plain text histogram:
Temperatures in January, 2006 in Purcellville,
Virginia
Frequency |
9---|
| 8 8
8---| |XXXXXXX|XXXXXXX|
| |XXXXXXX|XXXXXXX|
7---| |XXXXXXX|XXXXXXX|
| 6 |XXXXXXX|XXXXXXX|
6---| |XXXXXXX|XXXXXXX|XXXXXXX|
| |XXXXXXX|XXXXXXX|XXXXXXX|
5---| |XXXXXXX|XXXXXXX|XXXXXXX|
| |XXXXXXX|XXXXXXX|XXXXXXX|

12. 4---| |XXXXXXX|XXXXXXX|XXXXXXX|
| |XXXXXXX|XXXXXXX|XXXXXXX| 3
3---|
|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX|
|
|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX| 2
2---|
|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX|
| 1
|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX|
1 1
1---|
|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX|X
XXXXXX|XXXXXXX|XXXXXXX|
|
|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX|XXXXXXX|X
XXXXXX|XXXXXXX|XXXXXXX|
0-- .----|-------|-------|-------|-------|-------|-------|-------|------
-|
24.95 29.95 34.95 39.95 44.95 49.95 54.95
59.95 64.95
Temperatures (Degrees Fahrenheit)
(NOTE: If typing in plain text, use a fixed width font, such as
Courier New)

13. 1
6
8 8
3
2
1 1
0
1
2
3
4
5
6
7
8
9
25.95-
29.95

14. 29.95-
34.95
34.95-
39.95
39.95-
44.95
44.95-
49.95
49.95-
54.95
54.95-
59.95
59.95-
64.95
F
re
q
u
e
n
c
y
Temperature (degrees Fahrenheit)
30 Random Temperatures in January, 2006, Purcellville, VA

15. Page 4 of 6
MEDIAN:
When the 30 data values are sorted, since 30 is even, the median
is the average of the observations in the
middle, the average of the values in positions 15 and 16 in the
sorted list.
27.7 31.3 31.9 32.2 32.4 34.2 34.9 35.2 36.3 37.6 37.9 39.2 39.7
39.7 39.9
40.3 40.5 40.6 42.4 43.0 43.7 44.1 44.6 48.4 48.7 48.7 52.5 54.9
57.9 61.7
Median = (39.9 + 40.3)/2 = 40.1 degrees.
SAMPLE MEAN = �̅ = 1242.1/30 = 41.40 degrees = the sum of
the temperatures, divided by the
sample size
Note that the mean is larger than the median. The histogram has
a longer right "tail" compared to the left
end, due to a few relatively high temperatures. The mean is
affected by the size of the highest
temperatures, but the median is not, so the mean is larger than

16. the median.
RANGE = 61.7 - 27.7 = 34.0 degrees = the difference between
the maximum and minimum
SAMPLE VARIANCE = 66.1417 (calculations shown on the
next page; used a spreadsheet & pasted it in
the document)
SAMPLE STANDARD DEVIATION = s = 8.13 degrees
(calculation shown on the next page)
Data within one standard deviation of the mean must fall in the
interval
��̅ − �, �̅ + �� = �41.40 − 8.13, 41.40 + 8.13� = �33.27,
49.53�
Data within two standard deviations of the mean must fall in the
interval
��̅ − 2�, �̅ + 2�� = �41.40 − 2�8.13�, 41.40 +
2�8.13�� = �25.14, 57.66�
Data within three standard deviations of the mean must fall in
the interval
��̅ − 3�, �̅ + 3�� = �41.40 − 3�8.13�, 41.40 +
3�8.13�� = �17.01, 65.79�
__
__ 27.7 31.3 31.9 32.2 32.4 34.2 34.9 35.2 36.3 37.6 37.9 39.2

17. 39.7 39.7 39.9
40.3 40.5 40.6 42.4 43.0 43.7 44.1 44.6 48.4 48.7 48.7 52.5 54.9
___ 57.9 61.7 __
In the interval �33.27, 49.53�, there are 21 temperatures, and
21/30 = 70.0%
In the interval �25.14, 57.66� , there are 28 temperatures, and
28/30 = 93.3%
In the interval �17.01, 65.79� , there are 30 temperatures, and
30/30 = 100.0%
So, 70.0% of the temperatures fall within one standard deviation
of the mean, 93.3% of the temperatures
fall within two standard deviations of the mean, and 100% of
the temperatures fall within three standard
deviations of the mean. For a bell-shaped distribution, the
respective percentages are approximately 68%,
95%, and 100%. For the temperature data, the percentages are
reasonably close to the bell-shaped model,
so yes, the data distribution is approximately bell-shaped.
Page 5 of 6
Calculation of sample variance and sample standard deviation:

18. Col 1 Col 2 Col 3 Col 4 = [Col 3]^2
Count Temperature x x - Mean (x -
Mean)^2
1 44.1 2.6967 7.2720
2 31.3 -10.1033 102.0773
3 39.7 -1.7033 2.9013
4 40.6 -0.8033 0.6453
5 39.7 -1.7033 2.9013
6 35.2 -6.2033 38.4813
7 42.4 0.9967 0.9933
8 39.9 -1.5033 2.2600
9 40.3 -1.1033 1.2173
10 39.2 -2.2033 4.8547
11 52.5 11.0967 123.1360
12 43.7 2.2967 5.2747
13 43.0 1.5967 2.5493
14 37.9 -3.5033 12.2733
15 54.9 13.4967 182.1600

19. 16 48.4 6.9967 48.9533
17 57.9 16.4967 272.1400
18 34.9 -6.5033 42.2933
19 32.4 -9.0033 81.0600
20 37.6 -3.8033 14.4653
21 36.3 -5.1033 26.0440
22 44.6 3.1967 10.2187
23 40.5 -0.9033 0.8160
24 34.2 -7.2033 51.8880
25 32.2 -9.2033 84.7013
26 31.9 -9.5033 90.3133
27 27.7 -13.7033 187.7813
28 61.7 20.2967 411.9547
29 48.7 7.2967 53.2413
30 48.7 7.2967 53.2413
Sum 1242.1 1918.1097
Mean 41.40333333 Sample Variance 66.14171264
(divide Sum by 30) (divide Col 4 sum by 29, one less than the

20. sample size)
Sample Standard Deviation
(sqrt of variance) 8.132755538
Note: The results of the calculations can be checked by using
the spreadsheet functions var( ) and
stdev( ) in Excel. However, for the purposes of demonstrating
understanding of the calculations,
you must show work similar to the table above.
Page 6 of 6
CONCLUSION
In January, 2006 in Purcellville, Virginia, the 30 sampled
temperatures fell between 27.7 and
61.7 degrees, for a range of 34 degrees. Temperatures tended to
be concentrated in the upper
30’s and low 40’s, as shown the histogram.
The median temperature is 40.1° and the mean temperature is
41.4°, with standard deviation

21. 8.13°. The temperature data distribution is approximately bell-
shaped.
As mentioned at the beginning of this report, January of 2006
seemed to be unusually warm. The
analysis in this project agrees with this conjecture. In looking at
the website www.weather.com, I
found that the average daily HIGH temperature for January (in
any year) in Purcellville is 42
degrees. My analysis found an average of ALL sampled
temperatures (not merely the daily
highs) to be 41.4, not much below the typical daily high.
[Remark: The average of the data, 41.4, is a statistic – it is the
average temperature for the sample. It is possible that
the average of all January temperature readings is somewhat
different. If we were familiar with the techniques of
inferential statistics, we could assess whether we can take this
statistic and use it in making a statistical inference.]
FINAL REMARKS: This sample project could have been done
without the use of a spreadsheet or fancy
software, if the frequency distribution, and histogram were
carefully hand-drawn or typed. I have added
considerable commentary to the project items, to indicate what I
was thinking about when completing the tasks. You

22. can be less “wordy,” but be sure that your work and summary
are detailed and informative, and you show
calculations as requested.
Statistics Project (10% of course grade, due ___)
For this assignment, you will implement a project involving
statistical procedures. The topic may
be something that is related to your work, a hobby, or
something you found interesting. If you
choose, you may use the example described below.
The project report must include
• name of project and your name
• purpose of project
• data (provide the raw data used, and cite the source)—the
sample size must be at least
10. (The project example uses a random sample. Your sample
does not have to be
random. You could be collecting personal data, such as your
own bowling scores, and in

23. that case, the source is just your personal records.) Post a
summary of your topic and your data
here in the Statistics Project class conference (as a new topic).
Include a brief informative description
in the title of your posting.
• frequency distribution
• histogram
• median, sample mean, range, sample variance, and sample
standard deviation (show
work)
• percentage of data within one standard deviation of the mean,
percentage of data
within two standard deviations of the mean, percentage of data
within three standard
deviations of the mean (include explanation and interpretation -
-- do your percentages
imply that the histogram is approximately bell-shaped?)
• conclusion (several paragraphs interpreting your statistics and
graphs; relate to the
purpose of the project)
If you choose, you may use the following example for your
data.
• Purpose: Compare the amount of sugar in a standard serving
size of different brands of

24. cereal. (You may instead choose to compare the amount of fat,
protein, salt, or any other
category in cereal or some other food.)
• Procedure: Go to the grocery store (or your pantry) and pick at
least 10 different brands
of cereal. (Instead of choosing a random sample, you might
purposely pick from both the
"healthy" cereal types and the "sugary" ones.)
From the cereal box, record the suggested serving size and the
amount of sugar per serving. The
raw data is the serving size and amount of sugar per serving for
each of the 10 boxes of cereal.
Before calculating the statistics on the amount of sugar in each
cereal, be sure you are comparing
the same serving size.
If you use a serving size of 50 grams, you must calculate how
much sugar is in 50 grams of each
cereal. For example, if the box states that there are 9 grams of
sugar in 43 grams of cereal, there
would be 50 times 9 divided by 43, or 10.5 grams in 50 grams
of cereal. The result of this simple
calculation (for each of 10 boxes) is the data you will use in the
project statistics and charts.

25. Here is a Statistics Project Checklist:
* Title
* Your Name
* Purpose
*
Data (A set of at least 10 data values of a numeric quantity,
such as sugar per serving. Cite
the source. Label data as appropriate. For instance, Brand X:
10.5g per serving.)
*
Summary of Topic, and Data (posted in the Statistics Project
conference.) The
idea here is two-fold: (1) To share your interesting project idea
with your classmates, and (2)
To give me a chance to give you a brief thumbs-up or thumbs-
down before you finish the
project. Sometimes students get off on the wrong foot or
misunderstand the intent of the
project, and your posting provides an opportunity for some
feedback. Remark: Students may
use similar topics, but must have different data sets. For
example, several students may be
interested in points scored by a particular team, and that is fine,

26. but they must collect different
data, perhaps from different years.
*
Frequency Distribution (used for histogram; can do by hand, or
by using statistical
software)
* Histogram (can do by hand, or by using statistical software)
* Median (SHOW WORK/EXPLANATION)
*
Sample Mean (SHOW WORK/EXPLANATION; result can be
confirmed by using by
using statistical software)
* Range (SHOW WORK/EXPLANATION)
*
Sample Variance (SHOW WORK/EXPLANATION; result can
be confirmed by using
by using statistical software)
Make sure you are using the correct sample variance formula
when showing your
calculations.
*
Sample Standard Deviation (SHOW WORK/EXPLANATION;
result can be
confirmed by using by using statistical software)
*

27. Distribution of data: Calculate the percentage of data within one
standard deviation of
the mean, percentage of data within two standard deviations of
the mean, percentage of
data within three standard deviations of the mean (include
explanation and
interpretation). For a bell-shaped distribution, the respective
percentages are approximately 68%,
95%, and 100%. Do your percentages imply that your data
distribution is approximately bell-
shaped? Note that the answer could be Yes or No, depending on
your data. You can also look
at the shape of your histogram (is it roughly bell-shaped?) as
well as the percentages when
making your judgment.
*
Conclusion (A short narrative summary) Interpret your results
in a narrative summary
consisting of several paragraphs. Be sure to describe features of
the graphs and measurements
that you find to be important or interesting. )
You may submit all of your project in one document or a
combination of documents, which may consist of word
processing documents or spreadsheets or scanned handwritten
work, provided it is clearly labeled where each

28. checklist item can be found. Projects are graded on the basis of
completeness, correctness, ease in locating all
of the checklist items, and strength of the narrative portions.
Please see additional topics for Statistics Project Suggestions
and Tips, and for a completely-worked
Statistics Project Example.
---------------------------------------------
Project Suggestions and Tips
Suggestions for Topics: Look to your own experience and
interests for sample topics. Here are some popular
variables of interest, and data are relatively easy to collect:
• Temperatures (ex: set of high temperatures for a particular
location)
• Sports-related data or hobby-related data (ex: your most recent
12 bowling scores, points/runs scored
by a particular team for games in a specified time period)
• Gas prices in different geographic locations
• Breakfast cereal attribute (ex: calories per serving, or cost per
serving, carbohydrates per serving, etc.)
• Milk prices
• Stock price or Dow-Jones index for selected days
• Mileage rating (miles per gallon) for various vehicles
• Unemployment rates in various locales

29. • Salaries for a particular type of job (ex: teacher salary) in
various geographic locations
• Data compiled for some feature of an item (example: prices of
4&5-megapixel digital cameras
reviewed in Consumer Reports)
Tips:
• Remember that a sample size of at least 10 is required.
• If all of the data are virtually the same (example: 10 gas prices
and 8 of them nearly identical), then
there is little interest in carrying out descriptive statistics
techniques -- there isn't anything interesting to
learn from the analysis! So, your data should have some
variability.
• Make sure you are analyzing data related to a single variable.
For example, if your data consists of
15 unemployment rates for males and 15 unemployment rates
for females in 15 selected cities, then
you are working with two variables (male unemployment rate
and female unemployment rate), NOT
one variable as specified.
• For this project, it is NOT necessary that the data be drawn as
a random sample. (In the Statistics
Project example, the data do happen to be randomly selected, to
show you how it can be done, but
random sampling is not a requirement for this project.)
• Be sure that your graphs/charts are labeled appropriately, with
the axes, scales, and title easy to
interpret.

30. • Use the Statistics Project Checklist as an aid in making sure
your project meets all of the
specifications.
Statistics Project
For this assignment, you will implement a project involving
statistical procedures. The topic may be something that is
related to your work, a hobby, or something you found
interesting. If you choose, you may use the example described
below.
The project report must include
· name of project and your name
· purpose of project
· data (provide the raw data used, and cite the source)—the
sample size must be at least 10
· median, sample mean, range, sample variance, and sample
standard deviation (show work)
· frequency distribution
· histogram
· percentage of data within one standard deviation of the mean,
percentage of data within two standard deviations of the mean,
percentage of data within three standard deviations of the mean
(include explanation and interpretation --- do your percentages
imply that the histogram is approximately bell-shaped?)
· conclusion (several paragraphs interpreting your statistics and
graphs; relate to the purpose of the project)
If you choose, you may use the following example for your
data.
· Purpose: Compare the amount of sugar in a standard serving
size of different brands of cereal. (You may instead choose to
compare the amount of fat, protein, salt, or any other category
in cereal or some other food.)

31. · Procedure: Go to the grocery store (or your pantry) and pick at
least 10 different brands of cereal. (Instead of choosing a
random sample, you might purposely pick from both the
"healthy" cereal types and the "sugary" ones.)
From the cereal box, record the suggested serving size and the
amount of sugar per serving. The raw data is the serving size
and amount of sugar per serving for each of the 10 boxes of
cereal. Before calculating the statistics on the amount of sugar
in each cereal, be sure you are comparing the same serving size.
If you use a serving size of 50 grams, you must calculate how
much sugar is in 50 grams of each cereal. For example, if the
box states that there are 9 grams of sugar in 43 grams of cereal,
there would be 50 times 9 divided by 43, or 10.5 grams in 50
grams of cereal. The result of this simple calculation (for each
of 10 boxes) is the data you will use in the project statistics and
charts.