Part A (Items #1 and #12 are required but not graded)
You will submit one file, a Word document. Please limit each response to 250 words or less. Name the file in the following format: lastnamefirstinitialBTM8107-1.doc (example: smithbBTM8107-1.doc).
- Briefly describe your area of research interest (1-3 sentences is sufficient).
- List 4 variables that you might assess in a research project related to your research area. List one for each type of measurement scale: Nominal, ordinal, interval, and ratio. If you cannot think of a variable for each measurement scale, explain why the task is difficult.
- Create one alternate hypothesis and its associated null hypothesis related to your research area.
- Briefly describe whether you think your area of interest is more conducive to experimental or correlational research. What are the costs/benefits of each as it relates to your research area?
- Reliability vs. Validity. Considering your area of research interest, discuss the importance of reliability and validity. Can you have one without the other? Why or why not?
- Sample vs. Population. Considering your area of research interest, describe the difference between a sample and population. Why is it important to understand the difference between a sample and population in a statistics course?
- Measures of Central Tendency. Below is a set of data that represent weight in pounds for a particular sample. Calculate the mean, median and mode. Which measure of central tendency best describes this data and why? You may use Excel, SPSS, some other software program, or a hand calculator for this problem.
- Measures of Dispersion. For the data set above, calculate the range, the interquartile range, the variance, and the standard deviation. What do these measures tell you about the “spread” of the data?
- Descriptive Statistics. Why is it important to perform basic descriptive statistics prior to conducting inferential statistical tests?
- Statistical Significance. Revisit the hypotheses you created above in #5. If you conducted a statistical test based on these hypotheses and found a statistically significant result, what would that mean from both a statistical and practical standpoint? (Be sure to use the phrases “null hypothesis” and “effect size” in your answer).
- Type I and Type II Error. The concept of Type I and Type II Error is critical and will come into play not only with each and every statistical test you perform, but when you are asked to conduct an a priori power analysis for your Dissertation Proposal. Considering your answer to #10, discuss the implications of making both a Type I and Type II error.
- After completing Assignment #1, are there any areas of concern you have that you would like to share with your course instructor?