What is the distance between points P(-3, 5) and Q(3, 1)?
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What is the distance between points P(-3, 5) and Q(3, 1)?
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statistics
Introduction: Use the same scenario you submitted for the first assignment with modifications using your instructor’s f ...
statistics
Introduction: Use the same scenario you submitted for the first assignment with modifications using your instructor’s feedback, if needed. Include Table 1: Variables Selected for the Analysis you used in Assignment #1 to show the variables you selected for analysis. Table 1. Variables Selected for the Analysis Variable Name in data set Description Type of Variable (Qualitative or Quantitative) Variable 1: “Income” Annual household income in USD. Quantitative Variable 2: Variable 3: Variable 4: Variable 5: Data Set Description and Method Used for Analysis: Results: Variable 1: Income Numerical Summary. Table 2. Descriptive Analysis for Variable 1 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Income Median= SD = Graph and/or Table: Histogram of Income (Place Histogram here) Description of Findings. Variable 2: (Fill in name of variable) Numerical Summary. Table 3. Descriptive Analysis for Variable 2 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 3: (Fill in name of variable) Numerical Summary. Table 4. Descriptive Analysis for Variable 3 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 4: (Fill in name of variable) Numerical Summary. Table 5. Descriptive Analysis for Variable 4 Variable N Mean/Median St. Dev. Variable 4: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 5: (Fill in name of variable) Numerical Summary. Table 6. Descriptive Analysis for Variable 5 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Discussion and Conclusion. Briefly discuss each variable in the same sequence as presented in the results. What has the highest expenditure? What variable has the lowest expenditure? If you were to recommend a place to save money, which expenditure would it be and why? Note: The section should be no more than 2 paragraphs.
2 pages
Analysis Tally Results 1
1. Please calculate descriptive statistics on the following quantitative numbers AND create either a bar chart, stem and l ...
Analysis Tally Results 1
1. Please calculate descriptive statistics on the following quantitative numbers AND create either a bar chart, stem and leaf plot, or frequency table ...
Regression and Correlation analysis
Use the dependent variable (labeled Y) and one of the independent variables (labeled X1, X2, and X3) in the data file. S ...
Regression and Correlation analysis
Use the dependent variable (labeled Y) and one of the independent variables (labeled X1, X2, and X3) in the data file. Select and use one independent variable throughout this analysis. Use Excel to perform the regression and correlation analysis to answer the following.
Generate a scatterplot for the specified dependent variable (Y) and the selected independent variable (X), including the graph of the "best fit" line. Interpret.
Determine the equation of the "best fit" line, which describes the relationship between the dependent variable and the selected independent variable.
Determine the coefficient of correlation. Interpret.
Determine the coefficient of determination. Interpret.
Test the utility of this regression model, represented by a hypothesis test of b=0 using α=0.10. Interpret results, including the p-value.
Based on the findings in steps 1-5, analyze the ability of the independent variable to predict the dependent variable?
Compute the confidence interval for b, using a 95% confidence level. Interpret this interval.
Compute the 99% confidence interval for the dependent variable, for a selected value of the independent variable. Each student can choose a value to use for the independent variable (use same value in the next step). Interpret this interval.
Using the same chosen value for part (8), estimate the 99% prediction interval for the dependent variable. Interpret this interval.
What can be said about the value of the dependent variable for values of the independent variable that are outside the range of the sample values? Explain.
All DeVry University policies are in effect, including the plagiarism policy.
Project Part C report is due by the end of Week 7.
Project Part C is worth 100 total points. See grading rubric below.
Summarize your results from Steps 1–10 in a 3-page report. The report should explain and interpret the results in ways that are understandable to someone who does not know statistics.Submission: The summary report and all of the work done in 1–10 (Excel output and interpretations) as an appendixFormat for report:
Summary Report
Steps 1-10 addressed with appropriate output, graphs and interpretations. Be sure to number each step 1-10.
5 pages
Worksheet 4 07
1. The following set of data represents the number of crime rates and the guns sold in the year 2013. The mean number of c ...
Worksheet 4 07
1. The following set of data represents the number of crime rates and the guns sold in the year 2013. The mean number of crime rates was 16.5, with a ...
28 pages
STATISTICS: Logic of Hypothesis Testing
STATISTICS: Logic of Hypothesis Testing
A. Introduction
B. Significance Testing
C. Type I and Type II Errors
D. One- a ...
STATISTICS: Logic of Hypothesis Testing
STATISTICS: Logic of Hypothesis Testing
A. Introduction
B. Significance Testing
C. Type I and Type II Errors
D. One- and Two-Tailed Tests
E. Interpreting Significant Results
F. Interpreting Non-Significant Results
G. Steps in Hypothesis Testing
H. Significance Testing and Confidence Intervals
I. Misconceptions
J. Exercises
QSO 510 Southern New Hampshire University Cars Sold Regression Output HW
A finance manager employed by an automobile dealership believes that the number of cars sold in his local market can be pr ...
QSO 510 Southern New Hampshire University Cars Sold Regression Output HW
A finance manager employed by an automobile dealership believes that the number of cars sold in his local market can be predicted by the interest rate charged for a loan.
Interest Rate (%)
Number of Cars Sold (100s)
3
10
5
7
6
5
8
2
The finance manager performed a regression analysis of the number of cars sold and interest rates using the sample of data above. Shown below is a portion of the regression output.
Regression Statistics
Multiple R
0.998868
R2
0.997738
Coefficient
Intercept
14.88462
Interest Rate
-1.61538
Are there factors other than interest rate charged for a loan that the finance manager should consider in predicting future car sales?
Is interest rate charged for a loan the most important factor to be considered in predicting future car sales? Explain your reasoning.The dealership's vice-president of marketing has requested a sales forecast at the prevailing interest rate of 7%.
As finance manager, what reasons would you convey to the vice-president in recommending this forecasting model?
Is the prediction of car sales at 7% a reflection of the current downturn in the economy? How might this impact the dealership's business?
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Most Popular Content
statistics
Introduction: Use the same scenario you submitted for the first assignment with modifications using your instructor’s f ...
statistics
Introduction: Use the same scenario you submitted for the first assignment with modifications using your instructor’s feedback, if needed. Include Table 1: Variables Selected for the Analysis you used in Assignment #1 to show the variables you selected for analysis. Table 1. Variables Selected for the Analysis Variable Name in data set Description Type of Variable (Qualitative or Quantitative) Variable 1: “Income” Annual household income in USD. Quantitative Variable 2: Variable 3: Variable 4: Variable 5: Data Set Description and Method Used for Analysis: Results: Variable 1: Income Numerical Summary. Table 2. Descriptive Analysis for Variable 1 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Income Median= SD = Graph and/or Table: Histogram of Income (Place Histogram here) Description of Findings. Variable 2: (Fill in name of variable) Numerical Summary. Table 3. Descriptive Analysis for Variable 2 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 3: (Fill in name of variable) Numerical Summary. Table 4. Descriptive Analysis for Variable 3 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 4: (Fill in name of variable) Numerical Summary. Table 5. Descriptive Analysis for Variable 4 Variable N Mean/Median St. Dev. Variable 4: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Variable 5: (Fill in name of variable) Numerical Summary. Table 6. Descriptive Analysis for Variable 5 Variable n Measure(s) of Central Tendency Measure(s) of Dispersion Variable: Graph and/or Table. (Place Graph or Table Here) Description of Findings. Discussion and Conclusion. Briefly discuss each variable in the same sequence as presented in the results. What has the highest expenditure? What variable has the lowest expenditure? If you were to recommend a place to save money, which expenditure would it be and why? Note: The section should be no more than 2 paragraphs.
2 pages
Analysis Tally Results 1
1. Please calculate descriptive statistics on the following quantitative numbers AND create either a bar chart, stem and l ...
Analysis Tally Results 1
1. Please calculate descriptive statistics on the following quantitative numbers AND create either a bar chart, stem and leaf plot, or frequency table ...
Regression and Correlation analysis
Use the dependent variable (labeled Y) and one of the independent variables (labeled X1, X2, and X3) in the data file. S ...
Regression and Correlation analysis
Use the dependent variable (labeled Y) and one of the independent variables (labeled X1, X2, and X3) in the data file. Select and use one independent variable throughout this analysis. Use Excel to perform the regression and correlation analysis to answer the following.
Generate a scatterplot for the specified dependent variable (Y) and the selected independent variable (X), including the graph of the "best fit" line. Interpret.
Determine the equation of the "best fit" line, which describes the relationship between the dependent variable and the selected independent variable.
Determine the coefficient of correlation. Interpret.
Determine the coefficient of determination. Interpret.
Test the utility of this regression model, represented by a hypothesis test of b=0 using α=0.10. Interpret results, including the p-value.
Based on the findings in steps 1-5, analyze the ability of the independent variable to predict the dependent variable?
Compute the confidence interval for b, using a 95% confidence level. Interpret this interval.
Compute the 99% confidence interval for the dependent variable, for a selected value of the independent variable. Each student can choose a value to use for the independent variable (use same value in the next step). Interpret this interval.
Using the same chosen value for part (8), estimate the 99% prediction interval for the dependent variable. Interpret this interval.
What can be said about the value of the dependent variable for values of the independent variable that are outside the range of the sample values? Explain.
All DeVry University policies are in effect, including the plagiarism policy.
Project Part C report is due by the end of Week 7.
Project Part C is worth 100 total points. See grading rubric below.
Summarize your results from Steps 1–10 in a 3-page report. The report should explain and interpret the results in ways that are understandable to someone who does not know statistics.Submission: The summary report and all of the work done in 1–10 (Excel output and interpretations) as an appendixFormat for report:
Summary Report
Steps 1-10 addressed with appropriate output, graphs and interpretations. Be sure to number each step 1-10.
5 pages
Worksheet 4 07
1. The following set of data represents the number of crime rates and the guns sold in the year 2013. The mean number of c ...
Worksheet 4 07
1. The following set of data represents the number of crime rates and the guns sold in the year 2013. The mean number of crime rates was 16.5, with a ...
28 pages
STATISTICS: Logic of Hypothesis Testing
STATISTICS: Logic of Hypothesis Testing
A. Introduction
B. Significance Testing
C. Type I and Type II Errors
D. One- a ...
STATISTICS: Logic of Hypothesis Testing
STATISTICS: Logic of Hypothesis Testing
A. Introduction
B. Significance Testing
C. Type I and Type II Errors
D. One- and Two-Tailed Tests
E. Interpreting Significant Results
F. Interpreting Non-Significant Results
G. Steps in Hypothesis Testing
H. Significance Testing and Confidence Intervals
I. Misconceptions
J. Exercises
QSO 510 Southern New Hampshire University Cars Sold Regression Output HW
A finance manager employed by an automobile dealership believes that the number of cars sold in his local market can be pr ...
QSO 510 Southern New Hampshire University Cars Sold Regression Output HW
A finance manager employed by an automobile dealership believes that the number of cars sold in his local market can be predicted by the interest rate charged for a loan.
Interest Rate (%)
Number of Cars Sold (100s)
3
10
5
7
6
5
8
2
The finance manager performed a regression analysis of the number of cars sold and interest rates using the sample of data above. Shown below is a portion of the regression output.
Regression Statistics
Multiple R
0.998868
R2
0.997738
Coefficient
Intercept
14.88462
Interest Rate
-1.61538
Are there factors other than interest rate charged for a loan that the finance manager should consider in predicting future car sales?
Is interest rate charged for a loan the most important factor to be considered in predicting future car sales? Explain your reasoning.The dealership's vice-president of marketing has requested a sales forecast at the prevailing interest rate of 7%.
As finance manager, what reasons would you convey to the vice-president in recommending this forecasting model?
Is the prediction of car sales at 7% a reflection of the current downturn in the economy? How might this impact the dealership's business?
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