1. A college admissions department wants to determine if there is a relationship
ID: 3043528 • Letter: 1
Question
1. A college admissions department wants to determine if there is a relationship between students’ family income (annual income amount) and students’ SAT scores.
2. A child care center wants to determine if there is a relationship between how long a child naps (length of nap time in minutes) and incidents of aggression (how many aggressive outbursts a child experiences).
3. A researcher wants to determine if there is a relationship between media outlet (social media, newspapers, and radio) and interest in media by population group (youth, young adults, and older adults).
4. A nurse practitioner wants to determine if there is a relationship between a patient's allergic reaction to a vaccine and the site where she applies the vaccine (arm vs. leg).
5. A homeless shelter program wants to know if quality of life before the homelessness episode is related to whether or not homeless individuals will complete the intervention program (complete/non-complete). A quality of life measure is completed by homeless individuals prior to starting the intervention. The researchers hypothesize that those who complete the program had higher quality of life prior to becoming homeless.
6. A teen violence prevention program is providing mentorship to youth who report interpersonal violence in a relationship. Before starting the mentorship program youth are asked to complete a violence measure (used to compute a score). The mentorship program runs for 3 months. At the end of the three months the youth complete the same violence measure once more.
Options include independent t-test, dependent t-test, mean, ANOVA, Chi Square and correlation analysis.
Explanation / Answer
1. Variables: Family income (continuous variable) and SAT score (continuous variable)
Our goal is to study if there is a relationship between these to variables. That is we want to understand how much the family income is "correlated" with the SAT score. So in this case we will do a CORRELATION ANALYSIS.
2. Variables: Length of nap (continuous variable) and Number of incidents of aggretion (count variable)
Our goal is to study if there is a relationship between the two variables. So in this case also we will do a correlation analysis.
3. Variables: Interest in type of Media outlet (Categorical variable) and Population group (Categorical variable)
Our goal is to study whether these two variables are independent or are they related. Since the variables are categorical in nature we will do a CHI SQUARE test here.
4. Variables: Allergic reaction to vaccine (Categorical variable) and Site of application of vaccine (Categorical variable)
Our goal is to study whether the second variable has any impact on the first variable or not. So we will study whether the distribution of patients who took vaccine in the arm is homogeneous to that of patients who took vaccine in leg. We will do that by CHI SQUARE test.
5. Variables: Quality of life measure (continuous variable) and Status of completion of intervention program (Categorical variable)
Our goal is to test whether those who complete the program had higher quality of life prior to becoming homeless or not. That is we want to test the effect of a categorical variable on a continuous response. So we will do an ANOVA.
6. Variables: Violance measure before mentorship program (continuous variable) and Violance measure after mentorship program (continuous variable)
Our goal is to test if the mentorship program has any effect on violance. that is we want to test if the mean violance scores before and after the mentorship program are significantly different or not. Now it is logically obvious that the score of an individual before and after the program are dependent. So the two variables are dependent here. So we will do a DEPENDENT t-TEST..
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