A researcher wants to examine the relationship between time spend on social media (variable X) and loneliness (variable Y) in young adults. A randomly sample of n = 52 young adults was asked how much time in average they spend on social media each day and how lonely day feel on a typical day. The partial computations of collected data produced the following results: SP = -14 MX = 10 SSx = 36 MY = 16 SSY = 49 A. Based on these results, is there a significant correlation between time spend on social media and loneliness among young adults? Use a Pearson correlation test with p < .05, 2-tails to answer this research question. Follow the steps of hypothesis testing and insert your answers below. In your calculations,round all numbers to two decimal places to avoid rounding errors. ANSWER H0: H1: Computed Pearson r = df for decision about H0: Critical r-value used for decision about H0: Decision about H0 (i.e., reject or fail to reject): Conclusion (i.e., is there a significant correlation or not? If the correlation is significant, is it positive or negative? Make sure to follow the APA reporting format in your conclusion to avoid losing any points, see examples on the lecture slides.)
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
A researcher wants to examine the relationship between time spend on social media (variable X) and loneliness (variable Y) in young adults. A randomly sample of n = 52 young adults was asked how much time in average they spend on social media each day and how lonely day feel on a typical day.
The partial computations of collected data produced the following results:
SP = -14 MX = 10 SSx = 36 MY = 16 SSY = 49
A. Based on these results, is there a significant
Follow the steps of hypothesis testing and insert your answers below. In your calculations,round all numbers to two decimal places to avoid rounding errors.
ANSWER
- H0:
- H1:
- Computed Pearson r =
- df for decision about H0:
- Critical r-value used for decision about H0:
- Decision about H0 (i.e., reject or fail to reject):
- Conclusion (i.e., is there a significant correlation or not? If the correlation is significant, is it positive or negative? Make sure to follow the APA reporting format in your conclusion to avoid losing any points, see examples on the lecture slides.)
B. Find the regression equation for predicting a person's loneliness (i.e., variable Y) from the average time spend on social media each day (variable X). In your answer, show all computational steps.
Step by step
Solved in 2 steps
