University of La Verne Winter 2020 EXAM #4 XXXXXXXXXXNAME_______________________________ BUS500C XXXXXXXXXXGRADES _____________________________ Warning: While it is an open book, please work on the...

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University of La VerneWinter 2020 EXAM #4 NAME_______________________________ BUS500C GRADES _____________________________ Warning: While it is an open book, please work on the exam by yourself and do not communicate with anyone about the exam. Instruction: The final submission can either be in Excel or in this MS Word file or with both; your answers should be based analyzing the MS Excel file Happiness_2011.xls on the Happiness Survey under Exam 4; MS Excel file is organized with multiple datasheet for you in the Happiness_2011.xls file. In this exam, you can treat ordinal variables as interval variables. 1. Please Perform ANOVA One-Factor Analysis by doing the following (Hint: Chapter 12, ANOVA): a. Organize the data and show in MS Excel (5 points); b. Write down one question that you could answers using ANOVA One Factor analysis with the Happiness_2011.xls dataset and state its null and alternate hypotheses (5 points); c. Perform one ANOVA One-Factor analysis using two reasonable variables from the Happiness_2011.xls dataset (one quantitative variable and one qualitative group variable) and show the analysis results for the question (10 points); d. Indicate whether you reject or accept the null hypothesis (5 points); e. Interpret your findings from the analysis (5 points). Note: i. in Excel, you may use Sort function to select the data under different categories from the dataset, and then use the organized dataset to perform the analysis. ii. For one-way/factor ANOVA test, please watch the video under Chapter 12: One way/factor ANOVA: www.youtube.com/watch?v=leHOBf_-9kM) 2. Please Perform one Chi-square Test by doing the following (Hint: Chapter 15/17, Nonparametric Methods: Chi-Square): a. Organize the data and show in MS Excel (5 points); b. Write down one potential question that you could answers using Chi-square test with the Happiness_2011.xls dataset and state its null and alternate hypotheses (5 points); c. Perform one Nonparametric Methods: Chi-Square Test using any two reasonable variables from the Happiness_2011.xls dataset (two qualitative variables) and show the analysis results for the question (10 points); d. Indicate whether you reject or accept the null hypothesis (5 points); e. Interpret your findings from the analysis (5 points). Note: i. in Excel, you may use PivotTable function to build your contingency table from the dataset, and then use the table to perform the analysis. See Video under Chapter 1: How to build a PivotTable in Excel (optional): http://www.youtube.com/watch?v=7zHLnUCtfUk ii. For Chi-square test, please watch the video under Chapter 15/17:: Chi-Square Test  (Test of Contingency Table or Test for Independence) In Excel using data analysis: http://www.youtube.com/watch?v=WDLMhwuNATY 3. Please Perform regression analysis by doing the following (Hint: Chapter 13 on simple regression and 14 on multiple regression): a. Organize the data and show in MS Excel (5 points); b. Write down potential questions that you could answer using regression analysis for the Happiness_2011.xls dataset (5 points); c. Perform one simple regression using any two reasonable variables from the Happiness_2011.xls file (two quantitative variables) and show the analysis results (10 points); d. Interpret the findings from the simple regression analysis (5 points); e. Add one or more quantitative variable (including dummy variable that have values of 0 and 1) to the analysis in #b, perform one multiple regression analysis (10 points) f. Interpret your findings from the multiple regression analysis (5 points). Note: i. in Excel, you may copy the columns of the variables you want to analyze from the Happiness_2011 dataset and paste them next to each other in a new datasheet. ii. For simple regression analysis, please watch the video under Chapter 13: simple regression basics (Excel): http://www.youtube.com/watch?v=8JOJ_7R_OWY and its interpretation explanation  of simple regression: http://www.youtube.com/watch?v=c5blVUkkjTM iii. For multiple regression analysis, please watch the video under Chapter 14: Multiple regression analysis using Excel: http://www.youtube.com/watch?v=720_5tv_JDs and Multiple regression analysis interpretation: http://www.youtube.com/watch?v=i7ml3SbWd0w; Multiple regression analysis with dummy variables: http://www.youtube.com/watch?v=F0tRzIjDoTs
Answered Same DayMay 21, 2021

Answer To: University of La Verne Winter 2020 EXAM #4 XXXXXXXXXXNAME_______________________________ BUS500C...

Monali answered on May 22 2021
134 Votes
University of La Verne        Winter 2020
EXAM #4 NAME_______________________________
BUS500C                 GRADES _____________________________

Warning: While it is an open book, please work on the exam by yourself and do not communicate with anyone about the exam.
Instruction: The final submission can eit
her be in Excel or in this MS Word file or with both; your answers should be based analyzing the MS Excel file Happiness_2011.xls on the Happiness Survey under Exam 4; MS Excel file is organized with multiple datasheet for you in the Happiness_2011.xls file. In this exam, you can treat ordinal variables as interval variables.
Please Perform ANOVA One-Factor Analysis by doing the following (Hint: Chapter 12, ANOVA):
Organize the data and show in MS Excel (5 points);
Data of Level of Happiness and Level of EQ is organized in 3 levels. This is sorted and arranged in excel under tab of ANOVA.
Write down one question that you could answers using ANOVA One Factor analysis with the Happiness_2011.xls dataset and state its null and alternate hypotheses (5 points);
We can test if group on levels of Happiness is the same as groups on three levels of EQ. Logically, higher level of emotional quotient will lead to higher level of happiness. Therefore, we can check if there is difference in mean of three levels which are divided under two groups of happiness and EQ.
Null hypothesis: There is no difference between group of Happiness and EQ levels, µ1 = µ2
Alternative hypothesis: There is difference between groups of happiness and EQ levels, in other words it means, µ1 ≠ µ2
c. Perform one ANOVA One-Factor analysis using two reasonable variables from the Happiness_2011.xls dataset (one quantitative variable and one qualitative group variable) and show the analysis results for the question (10 points);
Summary of one-way ANOVA test is as below;
    SUMMARY
    
    
    
    
    Groups
    Count
    Sum
    Average
    Variance
    Happiness (Level)
    3
    101
    33.66667
    433.3333
    EQ (Level)
    3
    101
    33.66667
    97.33333
    ANOVA
    
    
    
    
    
    
    Source of Variation
    SS
    df
    MS
    F
    P-value
    F crit
    Between Groups
    0.0000
    1.0000
    0.0000
    0.0000
    #NUM!
    7.7086
    Within Groups
    1061.333
    4
    265.3333
    
    
    
    
    
    
    
    
    
    
    Total
    1061.333
    5
     
     
     
     
d. Indicate whether you reject or accept the null hypothesis (5 points);
Mean of both groups are equal = 33.667.
F critical value 7.7086 > F test value 0.00. Based on this null hypothesis cannot be rejected.
A large F ratio means that variation among group, by chance, is more than expected. In this case F- test calculated is 0.00. Therefore, based on mean both groups being equal and small F value, we conclude that there is no variation among group is not by chance.
e. Interpret your findings from the analysis (5 points).
Based on one-way ANOVA, we conclude that there is no different in groups of Happiness level and EQ levels. In other words, happiness and EQ would have the same effect across age.
Note:
i. in Excel, you may use Sort function to select the data under different categories from the dataset, and then use the organized dataset to perform the analysis.
ii. For one-way/factor ANOVA test, please watch the video under Chapter 12: One way/factor ANOVA: www.youtube.com/watch?v=leHOBf_-9kM)
2. Please Perform one Chi-square Test by doing the following (Hint: Chapter 15/17, Nonparametric Methods: Chi-Square):
a. Organize the data and show in MS Excel (5 points);
Two categorical variables are relationship and Health levels.
Relationship is divided into Divorced, Married, Separated, Never married and Married.
Health Level are divided into 4 with Healthy, Very Healthy, Poor health and Very Poor health.
Data is organized in Excel under tab of “Chi Square”
b. Write down one potential question that you could answers using Chi-square test with the Happiness_2011.xls dataset and state its...
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