Hypothesis Validity

There are a number of other variables in the data file, such as income, sex, age, and marital status. Create a hypothesis about an expected correlation. Here is an example: You might expect financially dependent people to have lower incomes. So, you would predict a negative correlation between DEPENDENCE and participant income (INC1). If you use SPSS to calculate the correlation between dependence and income, (ANALYZE>CORRELATE>BIVARIATE ) you get r = – .192, p < .001. This confirms the hypothesis and gives evidence for the validity of the Dependence scale.
Think of another relationship that might support the validity of one of the scales, and then test your hypothesis using the data. You will need to submit:
• Your validity hypothesis and a brief explanation about why you expect the hypothesis to be supported.
• The results of your statistical test of your validity hypothesis.
• Your conclusion about validity given the results of your statistical test.
The Quiz
The quiz has three short answer items. To provide your answers, first compute the variables per the instructions on the quiz link. Then, I suggest you spend some time in the data file looking at what the other measures are doing in the data file. For those less familiar with SPSS, if you click the variable view tab, and then slide the cells to be a little wider you can see the concept the variables are measuring, and when relevant, the values associated with each of the response options. I suggest doing this before doing quiz item #1.
Quiz item #1. Submit: Your validity hypothesis and a brief explanation about why you expect the hypothesis to be supported.
For Quiz item #2, please create a table or a write up summarizing your findings. DO NOT paste or attach SPSS output. You will get a zero (0) on that item if you do. SPSS output is never, ever, used as presented in the output file in professional writing.
For Quiz item #3 I have no further suggestions, simply follow the instructions in the course shell.

There are a number of other variables in the data file, such as income, sex, age, and marital status. Create a hypothesis about an expected correlation. Here is an example: You might expect financially dependent people to have lower incomes. So, you would predict a negative correlation between DEPENDENCE and participant income (INC1). If you use SPSS to calculate the correlation between dependence and income, (ANALYZE>CORRELATE>BIVARIATE ) you get r = – .192, p < .001. This confirms the hypothesis and gives evidence for the validity of the Dependence scale.
Think of another relationship that might support the validity of one of the scales, and then test your hypothesis using the data. You will need to submit:
• Your validity hypothesis and a brief explanation about why you expect the hypothesis to be supported.
• The results of your statistical test of your validity hypothesis.
• Your conclusion about validity given the results of your statistical test.
The Quiz
The quiz has three short answer items. To provide your answers, first compute the variables per the instructions on the quiz link. Then, I suggest you spend some time in the data file looking at what the other measures are doing in the data file. For those less familiar with SPSS, if you click the variable view tab, and then slide the cells to be a little wider you can see the concept the variables are measuring, and when relevant, the values associated with each of the response options. I suggest doing this before doing quiz item #1.
Quiz item #1. Submit: Your validity hypothesis and a brief explanation about why you expect the hypothesis to be supported.
For Quiz item #2, please create a table or a write up summarizing your findings. DO NOT paste or attach SPSS output. You will get a zero (0) on that item if you do. SPSS output is never, ever, used as presented in the output file in professional writing.
For Quiz item #3 I have no further suggestions, simply follow the instructions in the course shell.