Correlation Assignment

Pearson Correlation Coefficient Analysis and Cumulative Knowledge Question Student Name Institution Professor Name Course Date Pearson Correlation Coefficient Analysis and Cumulative Knowledge Question Problem Set 1: Pearson Correlation Coefficient Analysis CHANGE NUMBERSResearch Scenario: Fake reviews of online products have been on the rise over the last decade, where individuals or firms are paid to provide positive or negative reviews of products they have not actually purchased to sway future consumers. An industrial/ organizational psychologist at a large online retailer wants to determine whether there is a relationship between fake positive reviews (which present a product as probably better than it really is) and the number of customer returns. He records the number of positive reviews from unverified purchasers as well as the total number of times each product was returned over the course of 6 months. The data for twelve of these products are entered into the table below. Using this table, enter the data into a new SPSS data file and run a Pearson correlation coefficient analysis to test whether there is a relationship between the number of fake positive reviews for a product and the number of customer returns. Create a scatterplot to display the relationship between the variables. Remember to put your initials within any and all variable names. Follow the directions below the table to complete the homework.Problem Set 1: Pearson Correlation Coefficient Analysis CHANGE NUMBERSResearch Scenario: Fake reviews of online products have been on the rise over the last decade, where individuals or firms are paid to provide positive or negative reviews of products they have not actually purchased to sway future consumers. An industrial/ organizational psychologist at a large online retailer wants to determine whether there is a relationship between fake positive reviews (which present a product as probably better than it really is) and the number of customer returns. He records the number of positive reviews from unverified purchasers as well as the total number of times each product was returned over the course of 6 months. The data for twelve of these products are entered into the table below. Using this table, enter the data into a new SPSS data file and run a Pearson correlation coefficient analysis to test whether there is a relationship between the number of fake positive reviews for a product and the number of customer returns. Create a scatterplot to display the relationship between the variables. Remember to put your initials within any and all variable names. Follow the directions below the table to complete the homework. Fake Positive Reviews Total Number of Returns 67 19 23 78 12 52 26 30 10 87 41 40 5 10 2 21 3 9 8 8 1 11 11 6 1 Paste SPSS output. (10 pts) Correlations TJP_Fake Positive Reviews TJP_number of customer returns TJP_Fake Positive Reviews Pearson Correlation 1 .649* Sig. (2-tailed) .022 N 12 12 TJP_number of customer returns Pearson Correlation .649* 1 Sig. (2-tailed) .022 N 12 12 *. Correlation is significant at the 0.05 level (2-tailed). 2 Write an APA-style Results section based on your analysis. Include your scatterplot as an APA-style Figure, with figure number and title, as demonstrated in the Results Section presentation. (Results = 12 pts; Figure = 8 pts) Results The Relationship between the Number of Fake Positive Reviews for a Product and the Number of Customer Returns From the Pearson correlation coefficient analysis above, r = 0.649 and p = 0.022. The p value is less than the 0.05 significance level, suggesting that there is a significant relationship between the fake positive reviews for a product and the number of customer returns. On the other hand, since the r value of 0.649 is between 0.3 and 0.7, the fake positive reviews for a product and the number of customer returns have an approximately moderate positive linear relationship. Therefore, as the fake positive reviews for a product increase, the number of customers’ returns increases. Decision about the Null Hypothesis From the two-tailed significance test above, the hypotheses are as follows: H0: r = 0, meaning that the correlation coefficient of the fake positive reviews for a product and the number of customer returns is 0; hence, there is no relationship. H1: r ≠ 0, meaning that the correlation coefficient of the fake positive reviews for a product and the number of customer returns is not 0; hence, there could be a nonzero correlation. Problem Set 2: Pearson Correlation Coefficient AnalysisResearch Scenario: Recent research into the effects of climate-based events on mental health suggests that climate anxiety is on the rise, especially among younger people. A clinical psychologist would like to determine whether there is a relationship between age and climate anxiety. She administers the Climate Change Anxiety Scale (CCAS; Clayton, S., & Karazsia, B. T., 2020) to 22 adults between the ages of 18 and 65. Scores on the CCAS range from 22 to 110, with h...