This assignment consists of 3 parts (A, B, and C)
Section: Research Methods, Basic Statistics, and the Fundamentals of IBM SPSS Statistics
Week 1 Assignment: Reviewing Research Methods & Basic Statistics, Entering Data, and Analysis
Activity Due Date: 03/29/2015
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).
1. Briefly describe your area of research interest (1-3 sentences is sufficient).
2. 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.
3. Create one alternate hypothesis and its associated null hypothesis related to your research area.
4. 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?
5. 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?
6. 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?
7. 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.
8. 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?
9. Descriptive Statistics. Why is it important to perform basic descriptive statistics prior to conducting inferential statistical tests?
10. 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).
11. 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.
12. After completing Assignment #1, are there any areas of concern you have that you would like to share with your course instructor?
You will submit a total of three files: two SPSS data files and one Word document.
Section A: Creating a Data File.
Open a data file in SPSS and enter the data presented in Table 3.1 on page 101. Save this SPSS data file.
Section B: Create a mock research project.
Submit your answers to the three questions below in a Word document.
1. Considering your area of research interest, briefly state your area and a possible research project related to the area (150-500 words).
2. Pose one or more null and alternative hypotheses that follow from the possible research project.
3. List at least 10 variables that would be collected in your mock research project that would be used to answer the hypotheses. After each variable, list the variable name you will use in SPSS (Section C), the level of measurement (binary, nominal, ordinal, interval, or ratio), and the possible range of scores. Feel free to be creative.
Section C: Create a mock SPSS data set.
1. Open a data file in SPSS and enter in a set of mock data for the research project you describe in Section B. (Note: It is important that you do not collect real data for this activity; you cannot collect data without IRB approval).
2. You must enter 10 rows of data for each of the 10 variables (that is, create data for 10 mock participants). Each row represents the scores of each mock participant on the ten variables.
3. Participant #1 must have missing data for Variable #3. Ensure this is coded correctly.
You should now have three files for Part #2.
You will submit one Word document. You will create this Word document by exporting SPSS output into Word.
Section A. Creating Visual Displays of Data.
For this portion of the activity, you will export output you created while working in SPSS for Chapter 4 into a Word document. Please read the instructions below to ensure you are including the correct material in your document (This chapter has you create many charts and not all are required for Part #3).
1. Using the data set: DownloadFestival.sav, create a boxplot for males and females for the variable Day1. It is important that you change the outlier identified to 2.02 prior to creating the boxplot. Be sure to save the data set with a new name, indicating it is the corrected data set (outlier identified and corrected). Save this boxplot with an appropriate title in your Part #3 Word document.
2. Using the data set: ChickFlick.sav, create a simple bar chart for independent means. The variables you will use are: Arousal, Film, and Gender (grouping variable). Be sure to display error bars and save your chart with an appropriate title in your Part #3 Word document.
3. Using the data set: Hiccups.sav, create a clustered bar chart for related means. The variables you will use are: Baseline, Tongue Pulling, Carotid Artery Massage, Digital Rectal Massage. Be sure to display error bars, include labels for the X- and Y-axis, and save your chart with an appropriate title in your Part#3 Word document.
4. Using the data set: Text Messages.sav (Note: you may see an additional data set with the same name: TextMessages.sav – either will create the correct output), create a clustered bar chart for mixed designs. The variables you will use are: Time1, Time2, and Group. Be sure to display error bars, include labels for the X- and Y-axis, and save your chart with an appropriate title in your Part #3 Word document.
5. Using the data set: Exam Anxiety.sav, create a scatterplot that includes a regression line. The variables you will use are: Exam Performance and Exam Anxiety. Be sure to include the regression line and save your chart with an appropriate title in your Part #3 Word document.
Section B. Why Exploratory Data Analysis?
Write a short paragraph that highlights your understanding of why exploratory data analysis is a critical part of any analytical strategy (500 word limit). This answer is worth half the assigned points for this activity. To receive full credit, you must show a high level of understanding related to the importance of exploring data visually.
Utts, J. (2003)., May What educated citizens should know about statistics and probability. The American Statistician, 57(2), 74-79. http://www.ics.uci.edu/~jutts/AmerStat2003.pdf
Book Companion Site
Read Chapters 1, 2, 3 and 4
Field text companion site. Provides access to SPSS data files. http://www.sagepub.com/field4e/main.htm
Support your paper with a minimum of five (5) scholarly resources. In addition to these specified resources, other appropriate scholarly resources, including older articles, may be included. Length: 5 pages plus the SPSS Data Files requested on Parts B and C not including title and reference pages. Please be aware that you should allocate two pages for Part C section b
Your submittal should demonstrate thoughtful consideration of the ideas and concepts that are presented in the course and provide new thoughts and insights relating directly to this topic. Where applicable your submittal should reflect scholarly writing and current APA standards. Review APA Form and Style.
1.0 Review research methods and basic statistics as they relate to planning, conducting, and interpreting inferential statistics.
2.0 Develop appropriate null and alternative hypotheses given a research question.
3.0 Calculate and interpret descriptive statistical analysis.
4.0 Create and interpret visual displays of data.
7.0 Correlate how population, sampling, and statistical power are related to inferential analysis.
10.0 Demonstrate proficiency in the use of SPSS.