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.
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.
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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