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

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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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