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What are the appropriate levels of measurement for the iv and the dv?

by | Nov 13, 2022 | Other

 

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This is just a sample of what the exam will look like! Not the exam
This is the practice exam! This will be the format
SPSS Practice Exercise
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Directions: Open Data Set D. Complete the following questions. These are designed to be a practice for the SPSS exam. You may use books and notes to complete this exercise. For this exercise, you may work with a classmate as well. Refer to the handouts to help you answer these questions.
You have been given a data set that includes data on adults aged 35 years and older in upstate NY. Possible groupings of information include but are not limited to:
A heart health intervention (RN visits with programming on diet, physical activity and tobacco avoidance). The variable that denotes this intervention is q3 Group experimental or control (1= experimental and 2 = control). Other possible groupings would be q4 self-defined primary residence – with 3 levels (1 = rural, 2 = suburban, or 3 = urban), or q7 rural defined for research – 2 levels (1 = not rural, 2 = rural).
Pre and post physiologic data is available in several areas such as weight, cholesterol, BP readings etc. This fictitious intervention included nurses working with clients to develop a heart healthy diet and increase physical activity.
The purpose of the study was twofold: 1) describe the health risk factors of rural, suburban, and urban citizens of upstate NY and 2) to evaluate the effect of a nurse intervention program of heart healthy diet and physical activity on cardiovascular (CVD) risk factors. Weight was measured on a digital scale and recorded in pounds. Height was taken with a mechanical field stadiometer. BP was recorded in mmHg using a Stethoscope and a Sphygmomanometer. Cholesterol was measured using venous blood, and reported in mg/Dl. Depression symptomatology for the last week was measured with the CESD -9 short form. There are 9 items, each item can be scored 0 rarely or never or 1 sometimes or often. The items can be summed after re-coding two items with opposite direction answers to create a total CESD depression score. The higher the score, the more depression. Scores above 4 are correlated with a diagnosis of depression.
1. Provide a one-sentence problem statement for this research study. (e.g., statement of need–use your common sense and knowledge as a graduate student. no need for references here)
2. Frequency: choose a nominal demographic variable (eg. Q2 gender or q14 education), run the frequency, and create a bar chart.
3. Chi Square
1. Choose 2 variables with the appropriate level of measurement for Chi Square to analyze.
2. What is the appropriate test statistic?
3. Based on the 2 variables you chose, develop one research question (hint: look at the handout on formulating research questions).
4. Run the Chi Square analysis.
5. Based on the output, look in Cronk, p. 98-101 (version 8), to make sure you have met the assumptions and to report your findings. Be sure you have compared the calculated probability to the preset alpha.
4. Pearson’s Correlation Coefficient
1. Choose 2 variables with the appropriate level of measurement for Pearson’s Correlation Coefficient to analyze.
2. What is the appropriate test statistic?
3. Based on the 2 variables you chose, develop one research question (hint: look at the handout on formulating research questions).
4. Develop an appropriate hypothesis for your research question. What type of hypothesis is it (hint: look at the document about types of hypotheses) Do you think the hypothesis is feasible? Why or why not?
5. From the research question, identify the following:
1. Each variable
2. Whether the variable is independent, dependent, or research
3. The level of measurement for each variable
4. Operational definition for the dependent variable
6. Run the Pearson’s Correlation Coefficient analysis.
7. Based on the output, look in Cronk, p. 45-47, to report your findings. Be sure you have compared the calculated probability to the preset alpha and report the direction and strength of the correlation.
5. Practice reverse coding variables
1. Refer to the handout on re-coding a variable or to Cronk p. 17-18. You will need to reverse code q21 and q22 into q21r and q22r.
2. Where do you find the reverse coded variables? Sort them either ascending or descending.
3. Calculate the cesdtotr.
4. Since the range of scores for the cesdtotr is 0-9, how can you easily check to make sure that no score is greater than 9?
6. Independent t-test
1. What are the appropriate levels of measurement for the IV and the DV?
2. What is the appropriate test statistic?
3. Develop one research question based on an appropriate IV of your choice and the total cesdtotr score.
4. From the research question, identify the following:
1. Each variable
2. Whether the variable is independent, dependent, or research
3. The level of measurement for each variable
4. Operational definition for the dependent variable
5. What is an appropriate hypothesis and what type of hypothesis is it?
6. Run the Independent t-test analysis. Is this one tailed or two tailed?
7. Based on the output, look in Cronk, p. 62ff, to report your findings. Be sure you have compared the calculated probability to the preset alpha.
7. Dependent t-test (Paired t-test) There is a video on Panopto for dependent samples t-tests
1. What are the appropriate levels of measurement for the IV and the DV? Choose 2 variables that are appropriate.
2. What is the appropriate test statistic?
3. What is the difference between the independent and the dependent t-test?
4. Develop one research question and one hypothesis. Be sure they are formulated properly.
5. Run the Dependent t-test analysis. Is this one tailed or two tailed?
6. Based on the output, look in Cronk, p. 65ff, to report your findings. Be sure you have compared the calculated probability to the preset alpha.
8. One-Way ANOVA
1. What are the appropriate levels of measurement for the IV and the DV? Choose 2 variables that are appropriate.
2. What is the appropriate test statistic?
3. What is true about ANOVA? What further analysis is required if the ANOVA is significant?
4. Develop one research question and one hypothesis. Be sure they are formulated properly.
5. Run the ANOVA analysis. Is this one tailed or two tailed?
6. How do you know which groups are significantly different from each other if the ANOVA model is significant?
7. Based on the output, look in Cronk, p. 69ff, to report your findings. Be sure you have compared the calculated probability to the preset alpha. Will you accept or reject your null hypothesis?
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