Activity 3

Data Analysis and Interpretation. The most important section of a research paper is the part that deals with data analysis and interpretation. This process assigns the right meaning to the data that has been collected. Understanding the various parameters and variables identified in the research, testing the validity of a hypothesis, and drawing inferences is what makes data analysis the core of a research paper. This activity will help you understand the various methods of analyzing and interpreting data, to facilitate future research projects. Scenario 1 In order to understand the relationship between three variables A, B, and C, along with determining the strength of the relationship between them, a student conducted a correlation test on the following data set: A B C 0 2 2 12 6 9 2 7 3 10 5 6 4 On running the correlation analysis, the output displayed was as follows: A B C A 1 B 0.385951 1 C 0.882819 0.189722 1 Question 1 of 5 Which of the following interpretations is correct? A, B, and C have no correlation among them. a. Feedback: Not quite. This interpretation for the provided data set is not right. A and C have a high degree of positive correlation. b. Feedback: Yes. This interpretation of the provided data set is right.

A and B have a moderate degree of positive correlation. c. Feedback: Yes. This interpretation of the provided data set is right. A and C have a high degree of negative correlation. d. Feedback: Not quite. This interpretation for the provided data set is not right. B and C have a low degree of positive correlation. e. Feedback: Yes. This interpretation of the provided data set is right. Your answer is b. The correct answers are b, c and e. Scenario 2 Debt Income Unemployment Mean 1030.95 Mean 76.99 Mean 9.165 Standard Error 21.88684717 Standard Error 2.201457651 Standard Error 0.358305588 Median 1014 Median 75.3 Median 9.15 Mode 1133 Mode 78.3 Mode 9.3 Standard Deviation 97.88095616 Standard Deviation 9.845217915 Standard Deviation 1.602391305 Sample Variance 9580.681579 Sample Variance 9.845217915 Sample Variance 2.567657895 Kurtosis 0.888728877 Kurtosis 1.443827638 Kurtosis 0.956761892 Skewness 0.742206657 Skewness 1.228664539 Skewness 0.714114687 Range 397 Range 38.4 Range 6.6 Minimum 888 Minimum 65.1 Minimum 6.3 Maximum 1285 Maximum 103.5 Maximum 12.9 Sum 1285 Sum 103.5 Sum 12.9 Count 20 Count 20 Count 20 Question 2 of 5 Identify which tool has been used to analyze and present data in this scenario. Descriptive analysis. a.

Question 3 of 5 Which of the following interpretation is correct for the value of R Square? The use of social media has no significant impact on the depression among young adults. a. Feedback: Not quite. This is not the correct interpretation for the value of R-Square. The value of deviation from the mean is 93.29%. b. Feedback: Not quite. This is not the correct interpretation for the value of R-Square. The use of social media has a significant impact on the depression among young adults. c. Feedback: Yes. This is the correct interpretation for the value of R-Square. Any change in the use of social media will have 93.29% impact on the depression among young adults. d. Feedback: Yes. This is the correct interpretation for the value of R-Square. Your answers are c and d. The correct answers are c and d. Scenario 4 Elizabeth decided to study the impact of using algebra tiles to enhance the learning experience of autistic children. She identified two groups of students to participate in her study. One group used the algebra tiles while the second group received a traditional lecture approach. Question 4 of 5 Which test would you use to assess the difference between the mean scores for the two approaches? T-test for independent samples. a. Feedback: Yes. In order to establish any difference between two independent samples, this test is appropriate. T-test for dependent samples. b. Feedback: Not quite. Since these samples are independent, this test would not be appropriate. Correlation. c.

Feedback: Not quite. Correlation is used to establish the strength of relationship between two or more variables. Chi-square test. d. Feedback: Not quite. Chi-square is a test used to draw comparison between expectations and the observed data. Your answer is b. The correct answer is a. Scenario 5 Megan wants to conduct a study on the cost of treating clinical depression and the income of mental health patients at Sacred Heart Hospital. Her intention is to establish a relationship between the cost of treatment and the income of the patients. Megan also wants to generate a prediction report that reflects the adjusted cost of treatment. Question 5 of 5 Which method of data analysis would you suggest to Megan, for her to achieve her objectives? Descriptive analysis. a. Feedback: Not quite. Descriptive analysis only provides information about the central tendency values and the extent of deviation for the mean. Correlation. b. Feedback: Not quite. A correlation analysis will only establish the strength of the relationship between the two variables. Regression analysis. c. Feedback: Yes. A regression analysis, will provide the strength of relationship (R-square), the significant impact of one variable on another (through p value) and can generate a prediction report. Percentage analysis. d. Feedback: Not quite. Percentage analysis provided a comparative presentation of percentage changes in the variables.