Week 9 SPSS Discussion Instructions Here we discuss simple linear regression and create scatterplots with regression lines. This Photo by Unknown Author is licensed under CC BY-SA-NC This will be a...

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Week 9 SPSS Discussion Instructions Here we discuss simple linear regression and create scatterplots with regression lines. This Photo by Unknown Author is licensed under CC BY-SA-NC This will be a detailed discussion worth 15 points so plan accordingly.  Preparation: To prepare for this discussion, please follow along with our ScreenCast videos 16.7 and Required SPSS Videos 1. Stats 3e Screencast 16.7 (Click Here) 2. And for additional support, watch How to do Simple Linear Regression in SPSS (14-5) 1. Pay special attention to interpreting the residuals. Try to analyze and comment on the residuals in your report. Powerpoint Mini-Report General Guidance Welcome to our FINAL mini-report. To keep things interesting, we will use a PowerPoint format to simplify the writing and give you practice with presentations As a reminder, these mini reports of your results are designed to help you gain experience in data analysis and the interpretation and presentation of results, and we now add in some practice with presentations. The basic method here is the same as in the previous weeks where you begin by coming up with a possible scenario which would fit regression analysis, creating the mock data for your analysis, generating the results and charts in SPSS, and then writing up the results. By needing to come up with a question about relationships and enter data, you gain more of an understanding than if we just gave you a data set to analyze. However, if you want the challenge of analyzing new data sets, our text has many and the internet has a great number of real or fictitious data sets for you to practice on. The main difference in assignment format this week is that you will create a PowerPoint presentation of the results as you might do in a student conference. · We present these mini-reports as a discussion so everybody will be able to see multiple examples and therefore have a better idea of how to run statistical tests and write up the results.  If you are stumped on how to write your post, look at what others have written but change the example hypothesis and data to a scenario which interests you. · This will help accomplish our course themes/goals of 1) asking and answering questions with statistics, 2) telling stories with data, and 3) becoming ambassadors for statistics by learning how to explain concepts to other people and show them useful visualizations. Mini-Report Instructions To complete this assignment, please: 1) Create a scenario that would require the use of the simple linear regression. This means both variables must be interval or ratio scale data. Examples include looking at: · the relationship between the number of calories burned in a workout and the rating of hunger after the workout · the relationship between people’s satisfaction with life scores and their number of hours per year of volunteer work · The relationship between the number of hours of sleep people get per night and your choice of one test of cognitive function or ratings of general physical wellness (use validated measures for examples like these). Google for “validated test of…” to find examples or real scales or measurement tools. 2) write your research question and matching hypothesis (What is the relationship between X and Y.” Null hypothesis, “there is no relationship between X and Y”.) 3) generate fake/mock data, enter that correctly into SPSS – use at least 30 data points per variable. 4) calculate the useful descriptive statistics, histograms for each variable if you like, a scatterplot of your data that includes the regression line, and report both the the Pearson correlation coefficient (r) and regression coefficient (coefficient of determination, R2.), and the associated p-values. a. Verify that your data meet the assumptions of using regression (normally distributed, no outliers) by looking at your descriptive statistics. b. Verify that the “residuals” 5) and present your study as a PowerPoint presentation Your presentation should include 1. A Title slide which includes your name 2. (2 points) A research question, null/alternative hypothesis and variables slide 3. (3 pts) Method: One slide of methose mentioning: 1. sample size, sampling method, and measurement methods you might use to have collected the mock data for your study.  Use at least 30 data points per variable. 4. (3 pts) Results 1. One slide with a table of the mean, standard deviation, and skewness for each variable and one histogram for each variable 2. One slide with the scatterplot, its regression line, and copy/paste in the Anova and regression tables. 3. Write an APA formatted listing of the regression results and explain if the regression was significant or not. 5. (2 pts) Interpretation 1. Create one slide with a brief description of your results, an attention getting image, and what it means about your research question.  6. Create a references slide if needed After creating and inserting your presentation as an attachment in the discussion, please also add: 1) A comment on which method you like best for presenting results: a mini-report, an infographic, or a PowerPoint presentation 2) Please also attach your SPSS Viewer file and SPSS Data file with your post using the attachment button (the paperclip) from the discussion editor menu. The presentation is worth 10 points and your questions, file attachments, comments, and replies to classmates are worth the other 5 points in this forum. This discussion is worth 15 points.  The main post should be at least 500 words and please reply to at least 1 classmate. Help each other out as much as possible.
Answered Same DayApr 30, 2021

Answer To: Week 9 SPSS Discussion Instructions Here we discuss simple linear regression and create scatterplots...

Aimy answered on May 02 2021
132 Votes
Cups of Coffee & Sleep
Time spent on mobile before sleep & Sleep time
Research Question & Details

How do using mobile before bed time affects the number of minutes it takes one to sleep?
Null Hypothesis: There is no linear effect between before bedtime mobile use and time taken to sleep.
Alternative Hypothesis: There is linear effect between before bedtime mobile use and time taken to sleep.
Independent Variable: time in mobile (interval)
Dependent Variable: minutes_to_sleep (interval)
Methods
Sample Size: 50data points
Sampling method: Fake Data Generation; though one in a real-world study one would record timeused in mobile before bed time (vary randomly each day) and then record how many minutes it took them to sleep (there are devices that can track when one sleeps).
Measurement methods: time spent in...
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