Running head: INRODUCTION TO QUANTITATIVE ANALYSIS 1 Introduction to Quantitative Analysis 6 Introduction to Quantitative Analysis: Descriptive Analysis Walden University Introduction to Quantitative Analysis: Descriptive Analysis According to Frankfort-Nachmias and Leon-Guerrero (2018), descriptive analysis or descriptive statistics the procedure that is used to organize and describe data that were collected from a sample or population. When using descriptive statistics, Frankfort-Nachmias and Leon-Guerrero (2018) believes the best way to organize data are in a frequency distribution which is a table that provides the number of observations that belongs into each category of the variable that is being analyzed. For this week’s assignment, we will used one categorical variable and one continuous variable to execute the appreciate descriptive analysis that will cover central tendency and variability of both variables. Continuous Variable: Years Math Teacher Has Taught High School Math Statistics Years math teacher has taught high school math N Valid 17020 Missing 6483 Mean 10.14 Median 7.00 Mode 3 Std. Deviation 8.487 Minimum 1 Maximum 31 Percentiles 25 3.00 50 7.00 75 15.00 Categorical Variable: Parent Highest Level of Education For the categorical variable, there are six categories: less than high school, high school diploma/GED, associate’s degree, bachelor’s degree, master’s degree or decorate. Statistics T1 Parent 1: highest level of education N Valid 16784 Missing 6719 Mean 3.00 Median 3.00 Mode 2 Variance 1.892 Range 6 Percentiles 25 2.00 50 3.00 75 4.00 T1 Parent 1: highest level of education Frequency Percent Valid Percent Cumulative Percent Valid Less than high school 1342 5.7 8.0 8.0 High school diploma or GED 6795 28.9 40.5 48.5 Associate's degree 2562 10.9 15.3 63.7 Bachelor's degree 3893 16.6 23.2 86.9 Master's degree 1614 6.9 9.6 96.6 Ph.D/M.D/Law/other high lvl prof degree 578 2.5 3.4 100.0 Total 16784 71.4 100.0 Missing Missing 4 .0 Unit non-response 6715 28.6 Total 6719 28.6 Total 23503 100.0 Analysis of Data The first data presented is the continuous data with the variable: years math teacher has taught high school math. For continuous data, we presented the mode, median and mean, which represents the central tendency of distribution (Wagner, 2016). As we can see the mode- the area in which the largest frequency in the distribution- is 3 years, the median- the middle of the distribution is 7.0 years and the mean -or average- is 10.14 years. Frankfort-Nachmias and Leon-Guerrero (2018) states that the standard deviation provides a measurement of variation for interval-ratio and ordinal variables which or the expected value. In this case, the standard deviation is 8.487 years which is the extent of deviation for the teachers that taught math in high school. In examining the categorical variable, it’s great to see data that can be seen at quick glace like the level of educat ...

1. Running head: INRODUCTION TO QUANTITATIVE
ANALYSIS 1
Introduction to Quantitative Analysis 6
Introduction to Quantitative Analysis: Descriptive Analysis
Walden University
Introduction to Quantitative Analysis: Descriptive Analysis
According to Frankfort-Nachmias and Leon-Guerrero (2018),
descriptive analysis or descriptive statistics the procedure that
is used to organize and describe data that were collected from a
sample or population. When using descriptive statistics,
Frankfort-Nachmias and Leon-Guerrero (2018) believes the best
way to organize data are in a frequency distribution which is a
table that provides the number of observations that belongs into
each category of the variable that is being analyzed. For this
week’s assignment, we will used one categorical variable and
one continuous variable to execute the appreciate descriptive
analysis that will cover central tendency and variability of both
variables.
Continuous Variable: Years Math Teacher Has Taught High
School Math
Statistics
Years math teacher has taught high school math
N
Valid

2. 17020
Missing
6483
Mean
10.14
Median
7.00
Mode
3
Std. Deviation
8.487
Minimum
1
Maximum
31
Percentiles
25
3.00
50
7.00
75
15.00
Categorical Variable: Parent Highest Level of Education
For the categorical variable, there are six categories: less than
high school, high school diploma/GED, associate’s degree,
bachelor’s degree, master’s degree or decorate.
Statistics
T1 Parent 1: highest level of education

3. N
Valid
16784
Missing
6719
Mean
3.00
Median
3.00
Mode
2
Variance
1.892
Range
6
Percentiles
25
2.00
50
3.00
75
4.00
T1 Parent 1: highest level of education
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
Less than high school
1342

4. 5.7
8.0
8.0
High school diploma or GED
6795
28.9
40.5
48.5
Associate's degree
2562
10.9
15.3
63.7
Bachelor's degree
3893
16.6
23.2
86.9
Master's degree
1614
6.9
9.6
96.6
Ph.D/M.D/Law/other high lvl prof degree
578
2.5
3.4
100.0
Total
16784

5. 71.4
100.0
Missing
Missing
4
.0
Unit non-response
6715
28.6
Total
6719
28.6
Total
23503
100.0
Analysis of Data
The first data presented is the continuous data with the variable:
years math teacher has taught high school math. For continuous
data, we presented the mode, median and mean, which
represents the central tendency of distribution (Wagner, 2016).
As we can see the mode- the area in which the largest frequency

6. in the distribution- is 3 years, the median- the middle of the
distribution is 7.0 years and the mean -or average- is 10.14
years. Frankfort-Nachmias and Leon-Guerrero (2018) states that
the standard deviation provides a measurement of variation for
interval-ratio and ordinal variables which or the expected value.
In this case, the standard deviation is 8.487 years which is the
extent of deviation for the teachers that taught math in high
school.
In examining the categorical variable, it’s great to see data that
can be seen at quick glace like the level of education of each
parent. According to Frankfort-Nachmias and Leon-Guerrero
(2018), the measures of variability is the “numbers that describe
diversity or variability in the distribution of variable” (p. 94).
With the frequency distribution, we can examine the index of
qualitative variation (IQV) that shows the difference in the
group that is compared to the maximum number of possible
difference within the same distribution (Frankfort-Nachmaias &
Leon-Guerrero, 2018). In order to calculate this number, we
must know the number of observed difference divided by the
maximum possible difference. However, as we examine this
data, we know that high school diploma or GED is the highest
level of education that majority of the parents have. As a
practitioner of change, this data is important because we can
identify if parents with just a high school diploma encourages
others to pursue a high school diploma or do they encourage
others to do more.
Reference:
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social
statistics for a diverse society (8th ed.). Thousand Oaks, CA:
Sage Publications.
Wagner, W. E. (2016). Using IBM® SPSS® statistics for
research methods and social science statistics (6th ed.).
Thousand Oaks, CA: Sage Publications.

7. Running head: INRODUCTION TO QUANTITATIVE
ANALYSIS 1
Introduction to Quantitative Analysis 9
Introduction to Quantitative Analysis: Visually Displaying Data
Results
Walden University
Introduction to Quantitative Analysis: Visually Displaying Data
Results
According to Wagner (2016), a categorical variable is often
nominal or ordinal variable which provides small values of
names and labels, while continuous variable that are known as a
large values and factions. In reviewing the High School
Longitudinal Study dataset, one categorical and one continuous
variable will be identified and placed in the appropriate visual
display.
Categorical Variable: Parent Highest Level of Education
For the categorical variable, I will break this down into six
categories: less than high school, high school diploma/GED,
associate’s degree, bachelor’s degree, master’s degree or
decorate.
Continuous Variable: Years Math Teacher Has Taught High
School Math
For the continuous variable, I used the years math teacher has
taught high school math. This variable is continuous because it
can be broken down into decimals which can be infinite
(Wagner, 2016).

8. Analysis of Data
As I examine the data, both visual allowed to get a holistic view
of what’s being presented. For example, the first pie chart
identify the level of parent’s education. This allows us to see
quick data that majority of parents have a least a high school
diploma or GED. However, as I examine Wagner (2016) output
data, the data can be analyze by using descriptive functions
inside SPSS.
Case Processing Summary
Cases
Included
Excluded
Total
N
Percent
N
Percent
N
Percent
T1 Parent 1: highest level of education
16784
71.4%
6719
28.6%
23503
100.0%
Statistics
T1 Parent 1: highest level of education
N
Valid
16784

9. Missing
6719
T1 Parent 1: highest level of education
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
Less than high school
1342
5.7
8.0
8.0
High school diploma or GED
6795
28.9
40.5
48.5
Associate's degree
2562
10.9
15.3
63.7
Bachelor's degree
3893
16.6
23.2
86.9
Master's degree

10. 1614
6.9
9.6
96.6
Ph.D/M.D/Law/other high lvl prof degree
578
2.5
3.4
100.0
Total
16784
71.4
100.0
Missing
Missing
4
.0
Unit non-response
6715
28.6
Total
6719
28.6
Total
23503

11. 100.0
Years math teacher has taught high school math
N
Valid
17020
Missing
6483
Years math teacher has taught high school math
Frequency
Percent
Valid Percent
Cumulative Percent
Valid
1
1288
5.5
7.6
7.6
2
1611
6.9
9.5
17.0
3
1700
7.2
10.0

12. 27.0
4
1260
5.4
7.4
34.4
5
1098
4.7
6.5
40.9
6
888
3.8
5.2
46.1
7
795
3.4
4.7
50.8
8
713
3.0
4.2
55.0
9
599
2.5
3.5

13. 58.5
10
692
2.9
4.1
62.5
11
547
2.3
3.2
65.8
12
493
2.1
2.9
68.6
13
447
1.9
2.6
71.3
14
438
1.9
2.6
73.8
15
520
2.2
3.1

14. 76.9
16
357
1.5
2.1
79.0
17
275
1.2
1.6
80.6
18
248
1.1
1.5
82.1
19
276
1.2
1.6
83.7
20
356
1.5
2.1
85.8
21
179
.8
1.1

15. 86.8
22
242
1.0
1.4
88.3
23
264
1.1
1.6
89.8
24
144
.6
.8
90.7
25
219
.9
1.3
91.9
26
92
.4
.5
92.5
27
142
.6
.8

16. 93.3
28
141
.6
.8
94.1
29
137
.6
.8
95.0
30
146
.6
.9
95.8
31
713
3.0
4.2
100.0
Total
17020
72.4
100.0
Missing
Missing
50
.2

17. Unit non-response
6433
27.4
Total
6483
27.6
Total
23503
100.0
In examining this data, this longitudinal study explores
teenagers as they process through adulthood. We can clearly
identify the different levels of education of parents and
determine that a high school diploma were common among
them. However, if we look more in depth with the analysis of
data, some data is missing which can change the percentage of
levels. If we had not ran the report with SPSS, we would never
realize that some data were missing, can provide strong
possibilities but not 100% accuracy. However, in this sample
size, it give us a strong indicator that majority of parents have a
least a high school diploma.
As observed in the histogram, most math teachers taught high
school math for a least three years, but was it a full three year,
or three years and two weeks or months, etc. This analysis of
data shows how teachers in their field has years of expertise.
However, as we examine both data, one thing to consider is that
majority of people will finish high school and it’s important to

18. hire the right teachers to educate these individuals. Therefore,
one can say that the importance of a child’s high school
experience should be fill with intense knowledge of innovation
and solutions in increasing positive social change and
community awareness.
Reference:
Wagner, W. E. (2016). Using IBM® SPSS® statistics for
research methods and social science statistics (6th ed.).
Thousand Oaks, CA: Sage Publications.