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Advanced Quantitative Analysis Homework Help
Creating and Exploring SPSS Data
A. Create an
SPSS data set using the following information. Include screenshots of the data view, variable view and any procedures used.
1. In addition to inputting the data, make sure you format the columns in variable view if appropriate.
2. Binary categorical variables should be coded as dummy variables.
3. All variables except Student name should be numeric
Student 
Jimmy 
Peter 
Erica 
Jessica 
Melissa 
Joe 
Mark 
Carrie 
Maggie 
Jeremy 
Claudia 
Susan 
Paul 
Marital Status 
single 
married 
divorced 
divorced 
single 
single 
married 
single 
single 
married 
single 
married 
single 
Study:hours studied for exam 
2 
10 
0 
4 
7 
15 
4 
11 
3 
30 
6 
6 
9 
University 
UTEP 
NMSU 
UTEP 
UTEP 
NMSU 
NMSU 
NMSU 
UTEP 
NMSU 
NMSU 
NMSU 
UTEP 
NMSU 
Exam: Percent 
73 
82 
70 
94 
90 
88 
78 
82 
80 
98 
94 
85 
92 
Exam: Grade 
C 
B 
C 
A 
A 
B 
C 
B 
B 
A 
A 
B 
A 
Anexiety Score: Scale of 110 
9 
7 
5 
4 
3 
5 
2 
8 
4 
5 
6 
4 
4 
B. Perform the following on your newly created dataset (calculate=by hand/calculator, not using SPSS; illustrate your work)
1. Calculate and interpret the mean for the University dummy variable.
Mean = 1106/13 = 85.07692
2. For the exam Percent variable
a. calculate and interpret the mean, median and mode
Mean = 85.07692%
The Median is the 7th number when the numbers are arranged in ascending order. The median is equal to 85
Mode of the distribution is equal to 82, as it is the most common number
b. calculate the Standard Deviation
Standard deviation = 8.536
c. Calculate the 95% confidence interval for the mean (note small sample size)
95% confidence interval = (71.934, 99.436)
d. Calculate the zscores for Melissa, Joe and Jeremy.
Zscore for Melissa = 0.726
Zscore for Joe = 0.534
Zscore for Jeremy = 2.046
e. What is the probability that someone would score as high or higher than Melissa? What is the probability that someone would score in between Joe and Jeremy? (Hint: where do you go to find zscore probabilities?)
P (Score higher than Melissa) = 0.43
P (Score between Joe and Jeremy) = 0.622
Checking for Mean, Standard Deviations, Confidence Interval and Zscores
3. Now check your calculations for the variable Exam by having SPSS provide you with the mean, standard deviations, 95% confidence interval and zscores. Copy and paste any SPSS table as part of your answer and explain how you produced the results in SPSS.
Statistics 
Exam_percent 
N 
Valid 
13 
Missing 
0 
Mean 
85.0769 
Median 
85.0000 
Mode 
82.00^{a} 
Std. Deviation 
8.53875 
Skewness 
.265 
Std. Error of Skewness 
.616 
Minimum 
70.00 
Maximum 
98.00 
a. Multiple modes exist. The smallest value is shown 
Comparing Two Variables
C. Compare the two variables Tvhours (Hours of TV per day) and Sei (Socioeconomic Index).
1. Which of the two variables has a higher amount of variability. Explain how you reached your conclusion (hint: you need to account for the difference in the unit of measurement by using an equation explained in the lecture notes).
Descriptive Statistics 

N 
Minimum 
Maximum 
Mean 
Std. Deviation 
Skewness 
Statistic 
Statistic 
Statistic 
Statistic 
Statistic 
Statistic 
Std. Error 
HOURS PER DAY WATCHING TV 
987 
0 
24 
3.02 
2.675 
2.993 
.078 
RESPONDENT SOCIOECONOMIC INDEX 
1360 
17.1 
97.2 
49.843 
19.1702 
.464 
.066 
Valid N (listwise) 
926 






2. If we consider the mean as a model for summarizing the data, which variable’s mean, tvhours or sei, is a better fit of the data. Explain why.
D. Chart a frequency distribution (Histogram) for the tv hours watched (tvhours) and describe the distribution.
E. Createboxplots of respondents hours of tv watched (tvhours)by social class (class). You should have one graph with 4 side by side boxplots, one for each social class. Use the graphs to answer the following questions.
1. Which social class has the highest median hours of tv watching? Estimate this median from the graph.
2. Which social class has the highest interquartile range of tv watching? Estimate this interquartile range from the graph.
3. Describe the shape of the distribution of tv watching for the upper class.
Check your answers by obtaining the actual numbers using an SPSS procedure. Provide the results, including a screenshot of the output.
F. Explore the comparison further by examining how tv watching (tvhours) varies by both social class (class) and gender (sex). Create one bar chart which takes into consideration both gender and socioeconomic status. Based on the graph, explain the patterns in the data.
Running Analyses and Interpreting
Please continue to use the same dataset for questions 13. Provide information on how you completed the steps by including a description of the steps you took in constructing the analysis and screenshots.
Below you are given a series of research problems. Use the appropriate statistical technique to test the hypotheses. You will use a different SPSS procedure for each of the questions. The procedures we covered for this exam are OneSample TTest, Independent Sample TTest, and Crosstabs. You will use each of the 3 types of analysis at least once, however, so you might want to go through the exam first to determine which procedure you are going to use on which question. Make sure you thoroughly discuss the output and not just leave it up to my interpretation. Here are some guidelines for what you should cover in your answers. Make sure you revisit these for each question so you don’t forget what to include in your answer.
For all 3 research problems, you will need to
 Identify the IV and DV and the level of measurement for each. Assume a critical alpha of p<.05 for all 3 analyses.
 Identify which of the 3 statistical techniques you are using and explain why?
 State the null and research hypotheses (in words).
 Complete the analysis using the appropriate SPSS procedure. Provide screenshots of procedure and output.
 Make sure to identify the test statistic value and corresponding pvalue.
 Discuss whether the result is significant and whether you reject or fail to reject the null hypothesis. If significant, identify the probability that you just committed a type 1 error.
 Interpret the output by providing a statement about the relationship or lack of relationship between the variables and the direction of the result, if appropriate.
 If confidence intervals are given in the output, provide a statement interpreting the confidence interval.
In addition, for each specific technique, you will need to
Independent Sample TTest
• Assess the homogeneity of variance assumption (i.e. equal variances assumption) using the Levene’s test.
Crosstab with ChiSquare
• Check for significance across columns and within cell residuals.
• Provide and interpret at least one measure of association.
1. Two of your friends are arguing about whether married people are happier than nonmarried people. One friend believes that getting married makes people happier and the other one believes that once you are married life is a drag. You agree to settle their argument by examining the GSS dataset from your statistics class. Conduct your analysis with the variables “marital” and “happy”.
GENERAL HAPPINESS * MARITAL STATUS Crosstabulation 
Count 

MARITAL STATUS 
Total 
MARRIED 
WIDOWED 
DIVORCED 
SEPARATED 
NEVER MARRIED 
GENERAL HAPPINESS 
VERY HAPPY 
265 
25 
48 
5 
62 
405 
PRETTY HAPPY 
367 
74 
134 
20 
222 
817 
NOT TOO HAPPY 
54 
27 
48 
18 
77 
224 
Total 
686 
126 
230 
43 
361 
1446 
ChiSquare Tests 

Value 
df 
Asymptotic Significance (2sided) 
Pearson ChiSquare 
117.866^{a} 
8 
.000 
Likelihood Ratio 
117.256 
8 
.000 
LinearbyLinear Association 
82.414 
1 
.000 
N of Valid Cases 
1446 


a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 6.66. 
After explaining your results, you realize that this relationship might not be the same for men and women. Test to see if there is a conditional relationship. Explain your results.
2. One important area of study for sociologists is stratification, which includes patterns of inequality. One common way to operationalize inequality in sociology is socioeconomic status (in the GSS sei is an index constructed from a combination of questions regarding the individual’s occupation, education and income). Let’s use the GSS data to analyze patterns of income inequality.
Gender has historically been a strong predictor of inequality. Test the research hypothesis that women’s socioeconomic status (sei) is lower on average than men’s.
Group Statistics 


RESPONDENTS SEX 
N 
Mean 
Std. Deviation 
Std. Error Mean 

RESPONDENT SOCIOECONOMIC INDEX 
MALE 
597 
51.270 
19.9521 
.8166 

FEMALE 
763 
48.726 
18.4719 
.6687 

Independent Samples Test 

Levene's Test for Equality of Variances 
ttest for Equality of Means 
F 
Sig. 
t 
df 
Sig. (2tailed) 
Mean Difference 
Std. Error Difference 
95% CI of the Difference 
Lower 
Upper 
RESPONDENT SOCIOECONOMIC INDEX 
Equal variances assumed 
4.542 
.033 
2.434 
1358 
.015 
2.5447 
1.0h456 
.4935 
4.5958 
Equal variances not assumed 


2.411 
1230.576 
.016 
2.5447 
1.0555 
.4740 
4.6154 
The independent samples ttest was conducted whether the average value of socioeconomic value for women is lower than that of men. The Levene’s test for homogeneity of variances indicates that the assumption of homogeneity of variances is violated. The independent samples ttest indicate that the average socioeconomic value of women is less than that of men, t(1230.576) = 2.411, pvalue = 0.008 < 0.05.
3. The average age of the U.S. population is 37.7 years old. Test to see whether our sample is younger or older than the U.S. population.
OneSample Statistics 

N 
Mean 
Std. Deviation 
Std. Error Mean 
AGE OF RESPONDENT 
1433 
49.21 
17.563 
.464 
OneSample Test 

Test Value = 37.7 
t 
df 
Sig. (2tailed) 
Mean Difference 
95% Confidence Interval of the Difference 
Lower 
Upper 
AGE OF RESPONDENT 
24.818 
1432 
.000 
11.514 
10.60 
12.42 
The average age of a respondent is equal to 49.21 years. The one sample ttest indicates a test statistic, t(1432) = 24.818, pvalue < 0.001. Thus, at 0.05 significance level, we conclude that the sample in this problem is much older than the average person in the US