Category: Statistics homework help

Answer the following questions:
Which of the variables listed above (second paragraph) would you use to define success of sales employees in order to develop your model? (10 points) 
The choice of independent variables for your model has to be based on their power to predict the dependent variable AND their availability in job candidates’ resumes that you intend to screen.  Which of the variables listed above (second paragraph) would you test as predictors of success in your model? (10 points) 
Which parameter of the model, i.e., sensitivity, specificity, precision, or accuracy, describes the ability of your model to identify candidates who are actually qualified?  Which parameter of the model describes the ability of your model to identify candidates who are actually unqualified? Which parameter describes the ability of your model to correctly predict unknown candidates as being qualified?  (5 points) 
What are the false positive rate and the false negative rate? Describe what false positive and false negative mean.  (10 points)
If your goal is to develop a model to screen resumes and identify candidates to be invited for an interview, which type of error is worse – false positive or false negative? Explain the rationale for your answer. (10 points) 
If you want to improve the performance of your model to identify candidates to be invited for an interview, which parameter (sensitivity, specificity, precision, accuracy) would you use to guide the selection of candidates? Explain your rationale based on what you are trying to achieve with your predictions. (10 points)
If your goal is to develop a model to identify candidates who will receive a job offer, which type of error is worse – false positive or false negative? Explain the rationale for your answer. (10 points) 
If you want to improve the performance of your model to identify candidates to receive a job offer, which parameter would you use? Explain your rationale based on the what you are trying to achieve with your predictions. (10 points)
Fast forward one year.  The company deployed the model that you developed with the 3 years of data on current employees, and people were hired based on your predictions.  The Head of HR has now come back to you with a concern that not all of the new hires were “good”.  Twelve of the 100 people hired were not qualified, and did not work out.  What parameter in the confusion matrix would you use to understand if your model worked better than you expected, as well as you expected or worse than you expected?  How well did the model work?   Do you agree that accuracy not the best parameter to use?  If so, why not?   Explain the rationale for your answers.  (15 points) 
Describe any limitations and/or concerns associated with your approach for this new business opportunity. (10 points)
Point values for each question are stated above. Each question will be evaluated based on the following criteria:
Your ability to derive insights from the data provided.
The clarity of your logic, and the accuracy of your answers.

Instructions for Initial Post
1.) Reread your initial post from last week’s discussion board. Recall the topic you chose and the graphical representation you’ve already created. 
2.) Find two new sets of data within your same topic and create a different graphical representation (graph/chart) for each set of data. This means you will have three total graphical representations based on three different sets of data within the same topic. This also means that you should have 3 completely different types of graphs/charts (for example: one pie chart, one bar graph, and one line graph) with no repeated graph/chart types.
3.) Post all three graphical representations, including the one you made last week, into this week’s discussion board for your initial post. Post written summaries for each graphical representation, analyzing each in a thorough manner. You must make your initial post by Day 4 of the week, and you must cite the source of these data sets in your initial post, using proper APA formatting.

 
The research department of an appliance manufacturing firm has developed a new bimetallic thermal sensor for its toaster. The new bimetallic thermal sensor can sense the temperature of the bread and move the lever arm to activate the switch. The research department claims that the new bimetallic thermal sensor will reduce appliance returns under the one-year full warranty by 2%-6%. To determine if the claim can be supported, the testing department selects a group of the toasters manufactured with the new bimetallic thermal sensor and a group with the old thermal sensor and subjects them to a normal year’s worth of wear. Out of 250 toasters tested with the new bimetallic thermal sensor, 8 would have been returned. Seventeen would have been returned out of the 250 toasters with the old thermal sensor. As the manager of the appliance manufacturing process, use a statistical procedure to verify or refute the research department’s claim.
Instructions
Create 8-10 slides, including a cover and a sources list, for a presentation to the director of the manufacturing plant in which you:
Summarize the problem with the appliance manufacturing firm’s toaster.
Propose the statistical inference to use to solve the problem. Support your decision using a scholarly reference.
Using Excel:

Develop a flowchart for the proposed statistical inference, including specific steps.
Compute all statistical calculations.

Place your flowchart in a slide.
Determine if you can verify or refute the research department’s claim.
Choose sources that are credible, relevant, and appropriate. Cite each source listed on your source page at least one time within your assignment. 

Instructions for Initial Post
1.) Visit the following page: https://www.cdc.gov/DataStatistics/Links to an external site.
2.) Under “Data and Stats by Topic”, pick a topic you find interesting. Click on the topic. After you choose a topic be sure to put in that information in the previous page title PICK YOUR TOPIC HERE. Do not delete anyone else’s information on that page. Do not select a topic that has already been selected.
3.) Here, you will find a lot of data and information concerning your topic. You will pick a set of data and create a graphical representation for it, (i.e. a line graph, bar graph, pie chart). Make note: you MUST create your OWN graphical representation. Copied graphs DO NOT COUNT. You must cite the source of this data set in your initial post, using proper APA formatting.
4.) In your initial post, due by Day 4, you will introduce your topic and its importance along with discussing methodology and numerical findings in the data. You will also include your graphical representation and give a summary of it. You may post your graphical representation as an image directly into the textbox, copied from Excel or another program/website you used to generate it.

 This discussion is intended to help develop the skills needed to analyze and interpret statistical data.  Part of the analytical and interpretation process is being able to set aside our own biases and perceptions when examining the results.  Another part of the analytical and interpretation process is to not assert more than the data will support.  
Please attach the original PSPP output to your initial discussion post.  
1. Use PSPP to find the bivariate correlation between Per Capita State and Local Govt. Spending for Elem. and Second. Education: 2007 (EDS140) and the percent of the population with a Bachelor’s Degree or More (EDS154).  Report the following information:
     1A. Correlation:
     1B. Significance Level:
     1C. Is the relationship statistically significant? Explain. 
2. Use PSPP to find the bivariate correlation between Percent of the Population with a Bachelor’s Degree or More (EDS154) and State Minimum Wage Rates (EMS170). Report the following information:
     2A. Correlation:
     2B. Significance Level:
     2C. Is the relationship statistically significant? Explain.
3. What do the correlations tells us about government spending, education, and income? (Note: For statistically significant correlations, be sure to include in your explanation the size and direction of the correlation.)  Remember the null hypothesis is that there is no association. Answer as though your audience has little, if any, statistical knowledge.  The audience is most interested to learn what factors explain the correlation (or lack of a correlation).  

 
1.) Choose a topic of interest and find a graphical display of data on that topic of interest. The graphical display can be either a scatterplot, dot plot, bar graph, histogram, stem-and-leaf, pie chart, or box plot. You will need to cite the source of this display using proper APA format.
2.) Share why you chose this topic and summarize the graph (what did you find interesting, confusing, and/or helpful). Be sure to reference with in-text citations (author, date) when necessary and in APA format. See example below for correct APA referencing format:
Last Name, First initial. (date) Title of article in sentence format. Location of article such as or Journal in italics followed by volume, page # and doi when available 

 Instructions
Introduction:
One of the goals of this course is that you will be able to perform hypothesis tests. In this project, you will demonstrate your understanding of all the steps involved in testing a hypothesis test of μ when σ is unknown. Use the attachment for the Pearson Correlation Coefficient.
Directions:
Conduct the hypothesis test described further below. Write up the process and the results of the test in a professional-quality report using Microsoft Office. Include the following elements in your 1-2 page written report:
INTRODUCTION:
Describe the scenario and the reason why LEGO Group’s line manager should perform a hypothesis test.
BODY:
Include the following elements in the body of the report:
a) The name of the appropriate hypothesis test (e.g., “1 Sample Proportion Z test,” “1 Sample T-Test for Means”, etc.)
b) The null and alternative hypotheses. (Be sure to first define the parameter in context.)
c) Requirements check that justifies the use of the test:
i) Is the sample a simple random sample?
ii) Is the sample from a normal distribution, or does the Central Limit Theorem apply because ???? ≥ 30?
d) Give all the test details, including the sample statistic, the test statistics, the critical value, and the p-value.
e) Reject or fail to reject the null hypothesis
f) Report the conclusion of the hypothesis test in context.
g) Report and interpret the confidence interval estimate of the parameter in question
h) Weave in answers to any specific elements requested below.
4. CONCLUSION:
Write a brief conclusion to the report
5. After completing the report, save the Word document as a PDF and upload it to Data Analysis Project (KPA) dropbox on D2L.
SCENARIO:
The LEGO Group, an international company, makes the LEGO blocks that many of us have played with as kids. Many of its products require that the production process performs according to specifications. One of the products is Little People. The neck diameter of each of the Little People must be 0.5 inches so that it can be attached to the head properly. LEGO is interested in testing to see whether this process is performing according to specifications. If it is not functioning correctly, the LEGO Group will shut down the manufacturing process to fix the Little People machine.
The line manager takes a random sample of 40 Little People heads. The average diameter of the sampled necks is 0.48 inches, with a standard deviation of 0.05 inches. Is there sufficient evidence that the machine is not working correctly? Use a two-tailed hypothesis test with a significance level of α=0.02 to determine the answer.
Give the confidence interval estimate for the actual population neck size of Little People. Use a 98% confidence level so that it aligns with the hypothesis test in part 2.
Does “0.5 inches” appear in the confidence interval? Does the confidence interval estimate of the mean neck size, of Little People align with the conclusion of your hypothesis test? Explain why the two methods for estimating match or don’t.

 Instructions
Introduction:
One of the goals of this course is that you will be able to perform hypothesis tests. In this project, you will demonstrate your understanding of all the steps involved in testing a hypothesis test of μ when σ is unknown. Use the attachment for the Pearson Correlation Coefficient.
Directions:
Conduct the hypothesis test described further below. Write up the process and the results of the test in a professional-quality report using Microsoft Office. Include the following elements in your 1-2 page written report:
INTRODUCTION:
Describe the scenario and the reason why LEGO Group’s line manager should perform a hypothesis test.
BODY:
Include the following elements in the body of the report:
a) The name of the appropriate hypothesis test (e.g., “1 Sample Proportion Z test,” “1 Sample T-Test for Means”, etc.)
b) The null and alternative hypotheses. (Be sure to first define the parameter in context.)
c) Requirements check that justifies the use of the test:
i) Is the sample a simple random sample?
ii) Is the sample from a normal distribution, or does the Central Limit Theorem apply because ???? ≥ 30?
d) Give all the test details, including the sample statistic, the test statistics, the critical value, and the p-value.
e) Reject or fail to reject the null hypothesis
f) Report the conclusion of the hypothesis test in context.
g) Report and interpret the confidence interval estimate of the parameter in question
h) Weave in answers to any specific elements requested below.
4. CONCLUSION:
Write a brief conclusion to the report
5. After completing the report, save the Word document as a PDF and upload it to Data Analysis Project (KPA) dropbox on D2L.
SCENARIO:
The LEGO Group, an international company, makes the LEGO blocks that many of us have played with as kids. Many of its products require that the production process performs according to specifications. One of the products is Little People. The neck diameter of each of the Little People must be 0.5 inches so that it can be attached to the head properly. LEGO is interested in testing to see whether this process is performing according to specifications. If it is not functioning correctly, the LEGO Group will shut down the manufacturing process to fix the Little People machine.
The line manager takes a random sample of 40 Little People heads. The average diameter of the sampled necks is 0.48 inches, with a standard deviation of 0.05 inches. Is there sufficient evidence that the machine is not working correctly? Use a two-tailed hypothesis test with a significance level of α=0.02 to determine the answer.
Give the confidence interval estimate for the actual population neck size of Little People. Use a 98% confidence level so that it aligns with the hypothesis test in part 2.
Does “0.5 inches” appear in the confidence interval? Does the confidence interval estimate of the mean neck size, of Little People align with the conclusion of your hypothesis test? Explain why the two methods for estimating match or don’t.

 By the due date assigned, write a paper addressing the sections below of the research proposal.
Methodology
 Data Analysis Plans
 Describe plan for data analysis for demographic variables (descriptive statistical tests). Describe plan for data analysis of study variables (descriptive and inferential  statistical tests)

 
You’re a realtor with a client in the market for a 3+ bedroom home with at least 2 baths.  Randomly sample 10 homes from your original data set from Part A that meet these criteria.  Write a report that includes a linear regression model that predicts a home’s listing price based on its size (in square feet).  The use of EXCEL or other data software may be beneficial.
Write an introduction that includes the context of the data and precisely describes the sampling method used to achieve your random sample. Provide a data table that includes the 10 selected homes, their square footage, and their listing price. Calculate the mean and standard deviation for both square footage and price.
Create a scatterplot showing the association between the two variables. The scatterplot should include the least-squares line and a generic version of the regression equation.
Describe the association’s direction and form in context of the variables. Describe the strength of the association by providing a calculated correlation coefficient.
Provide a contextual version of the regression equation. Interpret the slope, intercept, and R2 of the model in context of the two variables.
Note any outliers or influential points in your scatterplot. Describe what might happen to your model if they were excluded.
Select one home from your list of 3+ bedroom, 2+ bathroom homes. Interpret the residual associated with this selection. Is the home a good deal, fair deal, or poor deal for your client?