Introduction to Quantitative Analysis: Confidence Intervals

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Description

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:

  • 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.
SPSS Assignment

This week you will compute Confidence Intervals, you should use an appropriate variable from the SAME 2 variables you used in Week 3 from the same data set, either the Afrobarometer or HSLS data set. To clarify, you will select only one of the two variables you used in Week 3. Think about the measurement level of your variable, make sure it is appropriate to compute a confidence interval for that level of measurement. Compute a 95% confidence interval for the mean of that variable.

**Unlike the discussion, you will use all of the cases in the assignment; Do Not take a random sample. This should make it easier!**

Include the SPSS output for your confidence interval in the paper. Be sure to include a figure caption in APA format for your output.

Write a one paragraph summary of the results of the confidence interval. This will be very brief.

Write a final, single, paragraph that explains the implications for social change.

Length
Limit your writing to 2 paragraphs, as described above.

User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

Explanation & Answer

Attached.

Week Four Summary

In this week, we will focus on the confidence intervals and their vital implications in statistical
analysis. We will use data given in the previous week and calculate different specified confidence
intervals. The confidence interval of the sample makes some inferences of the population in
reference to the variability in the data, the sample size and the confidence level impact on
different variables of the dataset (International Association for Statistical Computing, 2000). We
will generate random variables numbers in reference to the variables in the dataset and calculate
different confidence intervals.
The first set of the random variables contains 200 randomly selected variables from the afrobeter
dataset. The first table shows the 95% confidence intervals in reference to the variables:
problems with the health clinics, infrastructure index, lived poverty index, trust in the
government index and problems with the high schools. This table is accompanies by some stem
and leaf plots and corresponding charts.

Case Processing Summary
Cases
Valid
N

Missing

Total

Percent

N

Percent

N

Percent

30.0%

140

70.0%

200

100.0%

60

30.0%

140

70.0%

200

100.0%

(average index of 5 poverty 60

30.0%

140

70.0%

200

100.0%

60

30.0%

140

70.0%

200

100.0%

score=more 60

30.0%

140

70.0%

200

100.0%

Problems w/ Public Health
Clinics (higher scores=more 60
problems)
Infrastructure Index (higher
scores=greater
infrastructure)
Lived

Poverty

Index

items)
Trust in Government Index
(higher scores=more trust)
Problems w/ Public Schools
(higher
problems)

The following is the descriptive statistics table:
Descriptives
Statistic

Std. Error

Problems w/ Public Health Mean

4.1333

.54226

Clinics (higher scores=more 95% Confidence Interval for Lower Bound

3.0483

problems)

5.2184

Mean

Upper Bound

5% Trimmed Mean

3.8148

Median

3.0000

Variance

17.643

Std. Deviation

4.20035

Minimum

.00

Maximum

15.00

Range

15.00

Interquartile Range

6.00

Skewness

.972

.309

Kurtosis

-.031

.608

Infrastructure Index (higher Mean

13.9333

.38095

scores=greater

95% Confidence Interval for Lower Bound

13.1711

infrastructure)

Mean

14.6956

Upper Bound

5% Trimmed Mean

14.0185

Median

15.0000

Variance

8.707

Std. Deviation

2.95082

Minimum

5.00

Maximum

20.00

Range

15.00

Interquartile ...


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