Category: Statistics

1. Data on the amount of the customers’ shopping by using an account card and whether they decided to upgrade their account from silver status to platinum status after receiving the upgrade offer is shown in Table 2.
a. Construct the k nearest neighbors’ scheme for predicting upgrades based on the data given in Table 2, and interpret the confusion matrix.
2. According to the data given in part 1, estimate the probability of upgrade for each division of the purchase amount, using Bayes’ theorem.
using the book from Bowerman, B., Drougas, A. M., Duckworth, A. G., Hummel, R. M. Moniger, K. B., & Schur, P. J. (2019). Business statistics and analytics in practice (9th ed.). McGraw-Hill

Question 1: Hypothesis Testing (7 points, 1 point each)
The average performance of the statistical analysis course in UD is claimed to be 70 percent. To confirm the claim, the University took a samples of 30 students who took the course in the past and their marks are reported in the tables below (for respective group analysis): Sample For Group E:
72,73,66,72,70,74,69,67,75,78,65,73,70,67,71,74,69,72,70,76,67,71,74,69,73,72,70,75,73,71
Using the data assigned to your group undertake a hypothesis testing (at 0.05 level of significance) to determine whether the claim is true or not clearly showing all the steps below:
State the appropriate null and alternative hypotheses
Specify the desired level of significance, and state the sample size.
Determine the appropriate test statistic (Z-distribution or t-distribution) and state why.
Determine the critical values, for a = 0.05
Compute the test statistic from your sample.
Is the test statistic calculated in the acceptance or the rejection region (show it graphically)?
Make a decision and interpret the results.
Question 2: Regression Analysis (13 points: 2 + 2+ 3 + 3 + 3)
Use the house data, (available on Moodle) to
answer the following questions:
Run a linear regression where the dependent
variable is the rent value, while all the other variables are independent. Your group should work on the data sample assigned on the
excel TAB (posted in the Moodle).
a.
What is the Adjusted R Square? Interpret your result. (2 marks)
b.
Interpret the significance of each independent variable in explaining the
dependent variable. If significant, tell at what % level of significance. (4
marks)
c.
What is the estimated regression line? Interpret
the estimated coefficients for each of the independent variables. (5
marks)
d.
What will be the estimated rent-value of
a house with the following attributes:
(2
marks) SQFT
2300
AgeOfHouse
20

Using the steps developed in Value Stream Mapping (attached in the document named activity 3.2), go to 5 people (can be made up)  and ask how long it would take to do each step of your process. 
Using the data from this survey, determine the mean and sample deviation for each step. 
Enter this information in the Excel file attached for each step of your process. Run the program.
Using Minitab develop a Time Series Chart and a Descriptive Data table
Infer about the behavior and trend of values. 
Notes:  The values change each time you run the program. Therefore print the run that you will use as a basis for the current situation.
If you have more than 10 steps, insert the spaces you need and copy the columns.

Please use the attached lab, data and checklist to create the graphs and tables for the lab report. Compete a hypothesis and results section only with labeled graphs and tables. Use excel to create the graphs, instructions attached. Use JASP for the the statistical analysis, instrcuctions attached. 

Assignment
Choose a data set and work with the systematic sample that you create to complete this assignment. 
You will get feedback from your instructor on parts of the assignment in the parts listed. Use that feedback to improve that portion of the assignment
Part 1: Systematic Sample of your chosen Data Set
Part 2: Frequency Distribution
Part 3: Descriptive Statistics
Part 4: Semester Project First Half.
Part 5: 90% Confidence Interval for the Population Mean
Part 6: Hypothesis Test for the Population Mean
For this assignment you will submit the completed PowerPoint with the above information and what you learned about your sample. Download and use this Template Download Template for your assignment, change the file name to include your Name. Directions from the Project Parts assignments are below and in the template, click on the slide to expand. Additional details and examples for that portion are included in the respective assignment Part.
Images cannot be accepted for work for any portion of the assignment but may be used as supplemental explanations.
For any calculations that result in more than 4 decimal places, round to 4 decimal places. 
The General Layout is as follows (Click to expand each slide):
Slide 1: Title Page
Slide 2: Abstract
Slide 3: Your Sample Set
Slide 4: Frequency Distribution
Slide 5: Measures of Center
Slide 6: 5 Number Summary & IQR
Slide 7: Standard Deviation
Slide 8: 90% Confidence Interval for the Population Mean
Slide 9: Hypothesis Test
Slide 10: Conclusions
PreviousNext

Exploratory Data Analysis (Part A)
Introduction
Your instructor will provide you with a data file that includes data on five variables:
SALES represents the number of sales made this week.
CALLS represents the number of sales calls made this week.
TIME represents the average time per call this week.
YEARS represents years of experience in the call center.
TYPE represents the type of training the employee received.
Part A: Exploratory Data Analysis
Preparation
Open the files for the course project and the data set.
For each of the five variables, process, organize, present and summarize the data. Analyze each variable by itself using graphical and numerical techniques of summarization. Use Excel as much as possible, explaining what the results reveal. Some of the following graphs may be helpful: stem-leaf diagram, frequency/relative frequency table, histogram, boxplot, dotplot, pie chart, bar graph. Caution: not all of these are appropriate for each of these variables, nor are they all necessary. More is not necessarily better. In addition be sure to find the appropriate measures of central tendency, the measures of dispersion, and the shapes of the distributions (for the quantitative variables) for the above data. Where appropriate, use the five number summary (the Min, Q1, Median, Q3, Max). Once again, use Excel as appropriate, and explain what the results mean.
Analyze the connections or relationships between the variables. There are ten possible pairings of two variables. Use graphical as well as numerical summary measures. Explain the results of the analysis. Be sure to consider all 10 pairings. Some variables show clear relationships, while others do not.
Report Requirements
From the variable analysis above, provide the analysis and interpretation for three individual variables. This would include no more than 1 graph for each, one or two measures of central tendency and variability (as appropriate), the shapes of the distributions for quantitative variables, and two or three sentences of interpretation.
For the 10 pairings, identify and report only on three of the pairings, again using graphical and numerical summary (as appropriate), with interpretations. Please note that at least one pairing must include a qualitative variable and at least one pairing must not include a qualitative variable.
Prepare the report in Microsoft Word, integrating graphs and tables with text explanations and interpretations. Be sure to include graphical and numerical back up for the explanations and interpretations. Be selective in what is included in the report to meet the requirements of the report without extraneous information.
All DeVry University policies are in effect, including the plagiarism policy.
Project Part A report is due by the end of Week 2.
Project Part A is worth 100 total points. See grading rubric below.
Submission: The report, including all relevant graphs and numerical analysis along with interpretations
Format for report:
Brief Introduction
Discuss 1st individual variable, using graphical, numerical summary and interpretation
Discuss 2nd individual variable, using graphical, numerical summary and interpretation
Discuss 3rd individual variable, using graphical, numerical summary and interpretation
Discuss 1st pairing of variables, using graphical, numerical summary and interpretation
Discuss 2nd pairing of variables, using graphical, numerical summary and interpretation
Discuss 3rd pairing of variables, using graphical, numerical summary and interpretation
Conclusion
Part A: Grading Rubric
Category Points % Descriiption
Three individual variables – 12 point each 36 points 36% Graphical analysis, numerical analysis (when appropriate), and interpretation
Three relationships – 15 points each 45 points 45% Graphical analysis, numerical analysis (when appropriate), and interpretation
Communication skills 19 points 19% Writing, grammar, clarity, logic, cohesiveness, adherence to the above format
Total 100 points 100% A quality paper will meet or exceed all the above requirements
Part B: Hypothesis Testing and Confidence Intervals
Complete the following four hypotheses, using α = 0.05 for each. The week 5 spreadsheet can be used in these analyses.
1. Mean sales per week exceed 42.5 per salesperson
2. Proportion receiving online training is less than 55%
3 Mean calls made among those with no training is at least 145
4. Mean time per call is 14.7 minutes
Using the same data set from part A, perform the hypothesis test for each speculation in order to see if there is evidence to support the manager’s belief. Use the Eight Steps of a Test of Hypothesis from Section 9.1 of your text book as a guide. You can use either the p-value or the critical values to draw conclusions. Be sure to explain your conclusion and interpret that to the claim in simple terms
Compute 99% confidence intervals for the variables used in each hypothesis test, and interpret these intervals.
Write a report about the results, distilling down the results in a way that would be understandable to someone who does not know statistics. Clear explanations and interpretations are critical.
All DeVry University policies are in effect, including the plagiarism policy.
Project Part B report is due by the end of Week 6.
Project Part B is worth 100 total points. See grading rubric below.
Format for report:
Summary Report (about one paragraph on each of the four speculations)
Appendix with the calculations of the Eight Elements of a Test of Hypothesis, the p-values, and the confidence intervals. Include the Excel formulas or spreadsheet screen shots used in the calculations.

Steps to complete this homework:
Imagine you are the author of the attached DISSERTATION #1 (focus on pages 38-65). What would you have reported in your dissertation after learning all descriptive statistics: mean, median, mode, SD, variance, Min, Max, Range, kurtosis, skewness, confidence intervals… In this assignment, I want to see how you use these concepts (as many as possible) in your dissertation critique.
Specific Guidelines:
Read CHAPTER 4 of the attached DISSERTATION #1 (pages 38-65, where population characteristics and questionnaires were analyzed) carefully to see how qualitative or quantitative variables/data were summarized.
Choose only one of the scales (Multifactor
Leadership Questionnaire -MLQ, cognitive operator competencies questionnaire – COCQ, senior
leader competencies questionnaire – SLCQ, etc.) they used. 
Discuss the variables and the reason/logic why those descriptive statistics (frequency, mean, median, mode, standard deviation, skewness, kurtosis, etc.) were chosen for summarizing those variables.
Discuss the differences and similarities of how CHAPTER 4 is written compared to what should have been reported. Do you see any problems?
Sections in attached PDF textbook to use for the comparison:
Descriptive Statistics for Qualitative Data – PAGE 129
Descriptive Statistics for Quantitative Data – PAGE 138

2,000 words maximum essay using JAMOVI statistical software to conduct the necessary data analysis and graph creation for the essay. With a Sample size: >30 conduct Multiple linear regression; A continuous numerical dependent variable; Independent variables can be numeric and/or categorical; and Use cross sectional data only, NO time series/panel. Data analysis: R, R square, R square adjusted; T-test, F-test; Coefficient interpretation; and Model checking. The JAMOVI data file will also need to be submitted as part of the task. Please refer to Detailed Instruction in attached files for essay outline and other details required in the assignment.

Instructions are attached. Two sources are linked in the instructions, but you will need some outside sources as well (one for Topic 1 and another for Topic 2). Let me know if you  have any questions about the assignment.

This is an assignment you finished on April 24th as refrence for the powerpoint. 
I will do the recording myself and would appreciate speaker notes for recording.
If there are any questions than message me.