In your Week 2 Assignment, you displayed data based on a categorical variable and continuous variable from a specific dataset. In Week 3, you used the same variables as in Week 2 to perform a descriptive analysis of the data. For this Assignment, you will calculate a confidence interval in SPSS for one of the variables from your Week 2 and Week 3 Assignments.To prepare for this Assignment:Review the Learning Resources related to probability, sampling distributions, and confidence intervals.For additional support, review the Skill Builder: Confidence Intervals and the Skill Builder: Sampling Distributions, which you can find by navigating back to your Blackboard Course Home Page. From there, locate the Skill Builder link in the left navigation pane.Using the SPSS software, open the Afrobarometer dataset or the High School Longitudinal Study dataset (whichever you chose) from Week 2.Choose an appropriate variable from Weeks 2 and 3 and calculate a confidence interval in SPSS.Once you perform your confidence interval, review Chapter 5 and 11 of the Wagner text to understand how to copy and paste your output into your Word document.For this Assignment:Write a 2- to 3-paragraph analysis of your results and include a copy and paste of the appropriate visual display of the data into your document.Based on the results of your data in this confidence interval Assignment, provide a brief explanation of what the implications for social change might be.
confidence_intervals__skill_builder.pdf
sample_distributions__skill_builder.pdf
wk3assgn_quantitative_analysis_descriptive_analysis_.docx
wk2assgn_visually_displaying_data_results_.docx
afrobarometer_and_hs_longitudianal_study.zip
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Running head: DESCRIPTIVE STATISTICS
1
Descriptive Statistics
WK 3 Assignment
DESCRIPTIVE STATISTICS
2
Descriptive statistics provide brief explanatory summaries for data, which may be a
representation of the sample or the entire population. They assist in describing and understating
the basic features of the data by providing brief summaries about the data. Descriptive statistics
are grouped into measures of center and measures of spread (Wagner, 2016). This paper
explores the descriptive statistics for the HS Longitudinal dataset by focusing on Parent’s highest
level of education (X1PAR1EDU) and the Student’s scale of mathematics self-efficacy
(X1MTHEFF) variables(Norton, 2019).
Student’s scale of mathematics self-efficacy
Statistics
T1 Scale of student’s mathematics selfefficacy
N
Valid
18759
Missing
4744
Mean
Median
Mode
Std. Deviation
Variance
Skewness
Std. Error of Skewness
Range
Minimum
Maximum
.0421
.1000
.10
.99518
.990
-.377
.018
4.54
-2.92
1.62
The mean indicates the center of the data by revealing the most common/typical value in
a group of data while the median indicates the centermost value in a group of data arranged in
ascending order (Wagner, 2016). Notably, the mean score for the student math self-efficacy is
equal to 0.0421 and median of 0.10. The median is greater than the mean implying that the data
is negatively skewed. The mode indicates the most frequent score among the data which is 0.10.
DESCRIPTIVE STATISTICS
3
The standard deviation reveals the spread of the data around the mean (Wagner, 2016).
The standard deviation is 0.99518 indicating that scores are located within an average length of
0.99518 from the mean. The coefficient of skewness is -0.377 implying that the data is skewed to
the left. This can also be shown by a median greater than mean. The range shows spread by
providing the difference between the maximum and minimum values. Notably, the maximum
score is 1.62 whilst the minimum score is -2.92 resulting in a range of 4.54.
Parent’s highest level of education
Statistics
T1 Parent 1: highest
level of education
N
Valid
1
6784
Missing
6
719
T1 Parent 1: highest level of education
Frequenc
Valid
Cumulative
y
Percent
Percent
Percent
Valid
Less than high school
1342
5.7
8.0
8.0
High school diploma or
6795
28.9
40.5
48.5
GED
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
578
2.5
3.4
100.0
high lvl prof degree
Total
16784
71.4
100.0
Missing Missing
4
.0
Unit non-response
6715
28.6
Total
6719
28.6
Total
23503
100.0
DESCRIPTIVE STATISTICS
4
Notably, the largest group of students were those whose parents had a high school
diploma as the highest level of education representing 40.5% followed by a bachelor’s degree
with 23.2%. The histogram assumes a normal distribution indicating that a majority of the data is
concentrated at the center and narrowing at the tails. Additionally, this implies that a majority of
the parents had a high school diploma, associate degree or a bachelor degree as the highest level
of education.
The results of the data have an important effect on the social aspects of the community
and decision making. For instance, there comparatively lower number of students whose parents
DESCRIPTIVE STATISTICS
have less than a high school diploma as the highest level of education. This could imply that a
majority of those who have less than high school diplomas do not have the capacity to sustain
their kids through high school. As a result, policies can be made in order to address this social
problem.
5
DESCRIPTIVE STATISTICS
6
Reference
Wagner, W. E. (2016). Using IBM® SPSS® statistics for research methods and social science
statistics (6th ed.). Thousand Oaks, CA: Sage Publications.
Running head: VISUAL DISPLAY OF DATA
1
Visual display of data
WK 2 Assignment
VISUAL DISPLAY OF DATA
2
This report attempts to present the visual display of the High School Longitudinal study
dataset by focusing on one categorical variable and one continuous variable. In this case, the
categorical variable is the Parent’s highest level of education (X1PAR1EDU) and the Student’s
scale of mathematics self-efficacy (X1MTHEFF).
Categorical variable
The pie chart below indicates the visual representation of the categorical variable
(X1PAR1EDU);
Observably, a huge proportion of parents had a high school diploma as the highest level
of education representing 40.48% of all parents. Only 3.44% of parents had a Ph.D. or equivalent
to the highest level of education. This represents the lowest class among all the parents.
VISUAL DISPLAY OF DATA
3
Additionally, 23.19% of the parents had a bachelor’s degree as the highest level of education
representing the second largest class of parents.
Continuous variable
Statistics
T1 Scale of student’s mathematics
self-efficacy
N
Valid
18759
Missing
Mean
Median
Std. Deviation
Skewness
Std. Error of
Skewness
4744
.0421
.1000
.99518
-.377
.018
From the above results, the mean scale of math self-efficacy by the students is 0.0421 and
a median of 0.1. The median score is greater than the mean score indicating that the data is
VISUAL DISPLAY OF DATA
4
negatively skewed. This can also be shown by the histogram above in which the data slightly
lean to the left. A huge percentage of the students had a score of 0.1 in math self-efficacy.
The results above can be used in comparing the parent’s education level and the student’s
score on math self-efficacy. In this case if the parent’s education level is found to have
significant effect on student student’s self-efficacy score then policies can be formulated in
education sector to address social issue. For instance, students whose parents have low
educational qualification may require more attention in class compared to students whose parents
have high education level.
…
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