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PART IAstrologers assert that our birth dates influence our success (or lack thereof) in life. Test this assumption with the GSS08 data by analyzing the relationship between ZODIAC (Respondent’s Astrological Sign) with SEI (Respondent’s Socioeconomic Index). The SEI is an indicator of economic and social-economic attainment. The higher the SEI score, the more successful the respondent.

Run a descriptive analysis as you did previously (week 2) on SEI and ZODIAC- Use ‘Explore’ to get averages for the different zodiac signs (‘Dependent List’ = SEI; ‘Factor List’ = ZODIAC).
Create a table of the means and standard deviations for the 12 zodiac signs (in APA format- see instructional video below).
Conduct an independent samples t-test to see whether there is a difference in SEI between the zodiac signs of Taurus and Capricorn.
Write up the results of your t-test in APA format. Make sure you integrate the table in your text. 

What type of test did you use?
What variables did you examine?
What are the means and standard deviations of the variables?
What were your findings (please include t value, df, and p value)?
What do these results suggest?

PART IITest whether there is an association between a person’s educational attainment and how much television they watch. Use the GSS08 data set to perform an ANOVA on respondents’ highest educational degree (DEGREE) and the hours per day they watch television (TVHOURS).

Run a descriptive analysis on educational degree and the amount of television watched- Use ‘Explore’ to get averages for the educational degrees (‘Dependent List’ = TVHOURS; ‘Factor List’ = DEGREE).
Create a table of the means and standard deviations for the number of tv hours for the different degrees (in APA format).
Run an ANOVA to test whether there is a difference between the groups.
Write up the results of your ANOVA in APA format.  Make sure you integrate the table in the text.
What type of test did you use?
What variables did you examine?
What are the means and standard deviations of the variables?
What were your findings (please include df, F value, and p value)?
What do these results suggest?
Running Head: CORRELATION ANALYSIS 1

CORRELATION ANALYSIS 2

Correlation Analysis Comment by Laurie Slifka: Thanks for your submission!
Make sure you are using APA 7 title page for every assignment submitted in the graduate program. See example below.

https://apastyle.apa.org/style-grammar-guidelines/paper-format/title-page
Barbara Maclure
Quantitative Research
07/31/2021

Correlation Analysis

A study was conducted to determine the relationship between percent of the population that graduated from high school and the median earnings of male full-time workers. To determine this relationship, correlation analysis was conducted. Correlation test is suitable in examining a relationship between two or more quantitative variables. Comment by Laurie Slifka: Pearson’s correlation analysis

Variables examined

The variables used in this study were percent of the population that graduated from high school (EDS131) and median earnings of male full-time workers (EMS168). Comment by Laurie Slifka: Please put all in paragraph form

Results

SPSS was used to analyze the variables of interest and the results showed that the Pearson correlation between population that graduated from high school and earnings of male full-time workers was r = 0.30, p = 0.03.

Interpretation

The correlation shows a weak positive relationship between the two variables. Values between 0 and ±0.3 are considered weak, ±0.3 to ±0.5 moderate, ±0.5 to ±0.7 strong and ±0.8 to ±1 indicates a very strong relationship (Sweet, S, & Grace-Martín, K, 2012). This implies that an increase in the percentage of people graduating from high schools increases the median earnings of male full-time workers.
The p-value was 0.03 which shows a statistically significant relationship between the two variables since it is less than the significant level of 0.05. Comment by Laurie Slifka: Good

Data visualization

A graphical representation can be used to examine the relationship and the strength of the relationship. A scatterplot best describes the relationship. Figure 1 shows the results of the relationship between the two variables.
Figure 1: Correlation between variables

Comment by Laurie Slifka: Please use APA 7 format for title and figure number formatting
https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/apa_tables_and_figures.html

If the points do not follow any significant pattern, we conclude that there is no relationship between the two variables. When the plots follow an upward pattern from the origin to the right, we conclude the variables have a positive relationship. When the plots fall from top to the bottom right, the variables have a negative correlation. In this case, we can observe a positive but weak correlation between the variables.
Reference
Sweet, S, & Grace-Martín, (2012). Data Analysis with SPSS A First Course in Applied Statistics (4th ed) Allyn & Bacon