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BTM8107-8 WEEK 3

  • From Mathematics, Statistics
  • Due on 24 Jul, 2015 06:53:00
  • Asked On 15 Jul, 2015 06:57:12
  • Due date has already passed, but you can still post solutions.
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Create an MS Word document by cutting and pasting SPSS output into your document. Please answer the questions first and include all output at the end of the assignment in an Appendix. Name the file in the following format: lastnamefirstinitialEDU8006-3.doc (example: smithbEDU8006-3.doc).

Complete the following:

Part A
In Part A, you really getting to know a set of data and allows you the opportunity to perform statistical tests and then interpret the output. You will rely on all you have learned to this point and add correlation and regression strategies to your tool kit. 

Using the data set: Chamorro-Premuzic.sav; you will focus on the variables related to Extroversion and Agreeableness (student and lecturer).

  1. Exploratory Data Analysis.
    1. Perform Exploratory Data Analysis on all variables in the data set. Because you are going to focus on Extroversion and Agreeableness, be sure to include scatterplots for these combinations of variables (Student Agreeableness/Lecture Agreeableness; Student Extroversion/Lecture Extroversion; Student Agreeableness/Lecture Extroversion; Student Extroversion/Lecture Agreeableness) and include the regression line on the chart.
    2. Give a one to two paragraph write up of the data once you have done this.
    3. Create an APA style table that presents descriptive statistics for the sample.
  2. Make a decision about the missing data. How are you going to handle it and why?
  3. Correlation. Perform a correlational analysis on the following variables: Student Extroversion, Lecture Extroversion, Student Agreeableness, Lecture Agreeableness.
    1. Ensure you handle missing data as you decided above.
    2. State if you are using one or two-tailed test and why.
    3. Write up the results in APA style and interpret them.
  4. Regression. Calculate a regression that examines whether or not you can predict if a student wants a lecturer to be extroverted using the student’s extroversion score.
    1. Ensure you handle missing data as you decided above.
    2. State if you are using one or two-tailed test and why.
    3. Include diagnostics
    4. Discuss assumptions; are they met?
    5. Write the results in APA style and interpret them.
    6. Do these results differ from the correlation results above?
  5. Multiple Regression. Calculate a multiple regression that examines whether age, gender, and student’s extroversion predict if a student wants the lecturer to be extroverted.
    1. Ensure you handle missing data as you decided above.
    2. State if you are using one or two-tailed test and why.
    3. Include diagnostics
    4. Discuss assumptions; are they met?
    5. Write the results in APA style and interpret it.
    6. Do these results differ from the correlation results above?


Part B
Briefly restate your research area of interest.

  1. Pearson Correlation: Identify two variables for which you could calculate a Pearson correlation coefficient. Describe the variables and their scale of measurement. Now, assume you conducted a Pearson correlation and came up with a significant positive or negative value. Create a mock r value (for example, .3 or -.2). Report your mock finding in APA style (note the text does not use APA style) and interpret the statistic in terms of effect size and R2 while also taking into account the third variable problem and well as direction of causality.
  2. Spearman’s Correlation: Identify two variables for which you could calculate a Spearman’s correlation coefficient. Describe the variables and their scale of measurement. Now, assume you conducted a correlation and came up with a significant positive or negative value. Create a mock r value (for example, .3 or -.2). Report your mock finding in APA style (note the text does not use APA style) and interpret the statistic in terms of effect size and R2 while also taking into account the third variable problem and well as direction of causality.
  3. Partial Correlation vs. Semi-Partial Correlation: Identify three variables for which you may be interested calculating either a partial or semi-partial correlation coefficient. Compare/contrast these two types of analyses using your variables and research example. Which would you use and why?
  4. Simple Regression: Identify two variables for which you could calculate a simple regression. Describe the variables and their scale of measurement. Which variable would you include as the predictor variable and which as the outcome variable? Why? What would R2 tell you about the relationship between the two variables?
  5. Multiple Regression: Identify at least 3 variables for which you could calculate a multiple regression. Describe the variables and their scale of measurement. Which variables would you include as the predictor variables and which as the outcome variable? Why? Which regression method would you use and why? What would R2 and adjusted R2 tell you about the relationship between the variables?
  6. Logistic Regression: Identify at least 3 variables for which you could calculate a logistic regression. Describe the variables and their scale of measurement. Which variables would you include as the predictor variables and which as the outcome variable? Why? Which regression method would you use and why? What would the output tell you about the relationship between the variables?

You should now have the following file: lastnamefirstinitialEDU8006-3.doc (example: smithbEDU8006-3.doc)

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[Solved] part A and B both A+ money back guarantee

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  • Submitted On 16 Jul, 2015 03:33:34
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To complete Part A 1. Exploratory Data Analysis. a. Perform Exploratory Data Analysis on all variables in the data set. Because you are going to focus on Extroversion and Agreeableness, be sure to include scatterplots for these combinations of variables (Student Agreeableness/Lecture Agreeableness; Student Extroversion/Lecture Extroversion; Student Agreeableness/Lecture Extroversion; Student Extroversion/Lecture Agreeableness) and include the regression line within the chart. b. Compose a one to two paragraph write up of the data. c. Create an APA style table that presents descriptive statistics for the sample. a) For the variable Age Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Age 404 94.0% 26 6.0% 430 100.0% Here we can see that there are 404 are valid observation and 26 are missing observation Descriptives Statistic Std. Error Age Mean 19.60 .172 95% Confidence Interval for Mean Lower Bound 19.26 Upper Bound 19.94 5% Trimmed Mean 19.20 Median 19.00 Variance 11.888 Std. Deviation 3.448 Minimum 0 Maximum 43 Range 43 Interquartile Range 2 Skewness 2.350 .121 Kurtosis 17.989 .242 From the above analysis we see that the mean and median are approximately are equal but the difference are very small therefore we can say that the data distribution are approximately normal distribution. Also the data distribution are positively skewed and also leptokurtic. Tests of Normality Kolmogorov-Smirnova Shapiro-Wilk Statistic df Sig. Statistic df Sig. Age .279 404 .000 .600 404 .000 a. Lilliefors Significance Correction Data distribution test for normality is significant therefore the distribution of the data is normal. From the above histogram of the data we can say that the data is leptokurtic. From the above diagram we noticed that the data points lie around the straight line, from this point of view we can say that data distribution is normal. From the above figure we observed there are some outliers and mean and median are lies very closely therefore the distribution is normal. For the variable Gender Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Gender 424 98.6% 6 1.4% 430 100.0% There are 424 observed values and 6 missing values . Descriptives Statistic Std. Error Gender Mean .28 .022 95% Confidence Interval for Mean Lower Bound .23 Upper Bound .32 5% Trimmed Mean .25 Median .00 Variance .200 Std. Deviation .448 Minimum 0 Maximum 1 Range 1 Interquartile Range 1 Skewness 1.006 .119 Kurtosis -.993 .237 Here mean and median are approximately equal, the data distribution are approximately normal distribution also positively skewed and plateo kurtic. Tests of Normality Kolmogorov-Smirnova Shapiro-Wilk Statistic df Sig. Statistic df Sig. Gender .455 424 .000 .559 424 .000 a. Lilliefors Significance Correction The test for normality is significant. For the variable Student Neuroticosm Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Student Neuroticosm 420 97.7% 10 2.3% 430 100.0% Descriptives Statistic Std. Error Student Neuroticosm Mean 23.6262 .41985 95% Confidence Interval for Mean Lower Bound 22.8009 Upper Bound 24.4515 5% Trimmed Mean 23.6534 Median 24.0000 Variance 74.034 Std. Deviation 8.60431 Minimum .00 Maximum 44.00 Range 44.00 Interquartile Range 11.00 Skewness .005 .119 Kurtosis -.312 .238 Mean and median are approximately equal and data distribution is positively skewed and plateokurtic. Tests of Normality Kolmogorov-Smirnova Shapiro-Wilk Statistic df Sig. Statistic df Sig. Student Neuroticosm .042 420 .075 .993 420 .055 a. Lilliefors Significance Correction The normality test for the data is not significant. But from the q-q plot we can say that the data distribution are approximately normal. Also from the histogram data distribution is normal distribution. For the variable Student Extroversion Case Processing Summary Cases Valid Missing Total N Percent N...
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[Solved] BTM8107-8 WEEK 3

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  • Submitted On 17 Jul, 2015 05:08:48
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[Solved] BTM8107-8 WEEK 3

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  • Submitted On 23 Jul, 2015 08:34:38
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Part A In Part A, you really getting to know a set of data and allows you the opportunity to perform statistical tests and then interpret the output. You will rely on all you have learned to this point and add correlation and regression strategies to your tool kit. Using the data set: Chamorro-Premuzic.sav; you will focus on the variables related to Extroversion and Agreeableness (student and lecturer). Exploratory Data Analysis. Perform Exploratory Data Analysis on all variables in the data set. Because you are going to focus on Extroversion and Agreeableness, be sure to i...
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