Description Scenario You have been hired as a consultant by TC Ice Cream. As part of its expansion plan, TC Ice Cream wants to limit the number of flavors that they sell and only focus on those that are the most profitable. You will do an analysis of two flavors for a specific division and determine which flavor should be kept and which should be removed. Option A: Keep Flavor One Option B: Keep Flavor Two The TC Ice Cream management team has tasked you with doing an in-depth analysis to determine which of the two options will be the most profitable, given the monthly advertising expense range of $500–$2,750. Use the division that you selected in Module Two and select two flavors to make your recommendation. Consider the TC Ice Cream data set that contains data about quantity sold, advertising expenses, flavor rating, social media posts, and event promotions. You will use the same division and the same two flavors throughout the remainder of the course. Keep in mind that the “WEST NORTH CENTRAL” division cannot be used for your analysis. Your work here in Phase One is to do a current trend analysis, which will help you test your initial hypothesis as to which ice cream flavor has the most sales. You will use the work here as a foundation for Phase Two (in Milestone Two). Once you have completed the visualizations for the two flavors you selected, you will create a PowerPoint presentation analyzing the data. Prompt For this assignment, you will analyze the data from the TC Ice Cream data set and identify trends and patterns. You will submit an analysis report in the form of a PowerPoint presentation. You will also create multiple charts to present the descriptive analysis you performed. Within the TC Ice Cream Excel Workbook, you will use the sheets “Flavor One Analysis” and “Flavor Two Analysis” to create your visualizations. Select two flavors within the division you selected in Module Two. Complete the following visualizations for each flavor. The visualizations for Flavor One should be completed in the “Flavor One Analysis” sheet and the visualizations for Flavor Two should be completed in the “Flavor Two Analysis” sheet. It is recommended that you use pivot table filtering to filter the data to the specific division and flavor you have selected. Specifically, you must address the following rubric criteria: Excel Workbook Present the key descriptive statistics for the five quantitative variables in a table (quantity sold, advertising expenses, flavor rating, social media posts, and event promotions). The key descriptive statistics include the mean, median, standard deviation, and range. Analyze the TC Ice Cream data to identify trends and patterns for the two flavors you have selected. For each flavor, create the following visualizations. Create a line chart (also known as a trend chart) using the qualitative variable Date and the quantitative variable Quantity Sold to provide a visualization displaying quantity sold by month. Create a line chart (also known as a trend chart) using the qualitative variable Date and the quantitative variable Flavor Rating (average) to provide a visualization displaying flavor rating (average) by year/quarter/month. Create a combo chart using the qualitative variable Date (x-axis) and the quantitative variables: Quantity Sold (clustered column) and Advertising expenditures (line - secondary axis). Create a combo chart using the qualitative variable Date (x-axis) and the quantitative variables: Quantity Sold (clustered column) and total – Social Medial Posts and Event Promotions (line - secondary axis). Hint: create a pivot table variable to sum the social media posts and event promotions. Create a box and whiskers chart using the qualitative variable Quantity Sold. This will help identify any outliers in the quantity sold data. Create a histogram for the quantitative variable Flavor Rating. It is recommended to use the data analysis “add-in” and the analysis tool “Histogram” to create the data for the visualization. PowerPoint Presentation Using the Milestone One PowerPoint Template, complete the following: Outliers: Identify any outliers that you see and explain how they have an impact on the overall trends. Outliers are the data points that can have an impact on your averages and basic descriptive analysis. Analysis: Form and explain your initial hypothesis based on your analysis of the charts and trends in Excel. Which option (Option A or Option B) would you choose at this point in your analysis, given the monthly expense range of $500–$2,750? Why did you choose your selected attributes? Describe any relationships or trends you observed while conducting your analysis. Your presentation should include key visualizations and analysis to support your report. What to Submit TC Ice Cream Excel Workbook: Submit the TC Ice Cream Excel Workbook. For this assignment, work should be completed in the “Flavor One Analysis” and “Flavor Two Analysis” sheets. Do not remove any sheets from the workbook. PowerPoint Presentation: Submit a PowerPoint presentation using the Milestone One PowerPoint Template. Any sources should be cited in APA format. Consult the Shapiro Library APA Style Guide for more information on citations.
Description Discussion Topic: You are now at the halfway point in the course. Name at least one challenge you have faced in the course so far, and describe how you coped with this challenge. To Access My School/Course you’ll have to follow the steps below. Let me know when you’re ready to login so I’ll be ready to send you the required code immediately upon receipt. Go to https://auth.columbiasouthern.edu/login?service=https://mycsu.columbiasouthern.edu/Account/LogOn Select Blackboard If the link above doesn’t give you the Blackboard option, just Google “Columbia Southern University Login” and click on the link that pops up A message will pop up asking to Approve sign in request: Click “I can’t use my Microsoft Authenticator App right. now” A message will pop up asking to Verify Identity: Click on “Text +Xxxxxxxxx16 (I’ll receive the code immediately and will message it to you). Enter the code I send you and select the option “Do not ask me this again for 7 days”. Now you should be logged in. If an error message pops up saying you don’t have access, just log back in and it should work from there.
Description You must show complete work to be considered for full credit. For each question, use the specified format: manually or SPSS or both. Compile work into a single Word or pdf document. Copy and paste on answer document only relevant SPSS output with the exact answer highlighted. Never submit direct SPSS output as answer to a question.
Description example answer: Class, I used Data set 17 Mean: 4.77 Standard Deviation=$1.47 E Value= $0.53 95% Confidence Interval= $4.24- $5.30 Confidence Intervals For this forum we will discuss confidence intervals and what they mean. Initial Post Instructions: Choose a data set of fuel prices from the attached Excel file. Find the mean and standard deviation for the data set. Please do not try to do this by hand, but use the functions in Excel. Find the 95% Confidence Interval for your data. Response Post Instructions: Respond to two of your classmates by analyzing what the confidence interval means in this scenario and how this data can be used. And then compare how the results vary between the different data sets. Sample initial post: First find the mean and standard deviation. (Refer to video in week 2 discussion.) Then type this in an excel cell =confidence.norm(0.05,stdev,samplesize)and hit enter. This is the E value. (Note: please use your standard deviation and sample size and not the words.) Set up your confidence interval: (mean-E, mean+E) It is important to go back and read follow up responses from your instructor. Formula you used above for the confidence interval: The formula is E= zsubc * sigma / sqrt n Where the left hand endpoint is xbar - E and the right hand endpoint is xbar + E To earn full credit for this discussion, you must respond to at least two (2) of your peers and post your initial post by Thursday.
Description Dr. Rose was interested in studying student involvement in extracurricular activities, residence, school motivation scores, life satisfaction scores, and their scores on exams 1, 2, and 3. He found that students were either (0) not involved with extra-curricular activities on campus or (1) involved with extracurricular activities and either lived (1) on campus, (2) off-campus, or (3) with their parents. Using these data Lab 1.omv Download Lab 1.omv, please answer the questions below and provide your Jamovi file with analyses completed. Be sure to open the Jamovi software FIRST and then open the file within the Jamovi software. Here is a Step-by-Step Guide Actionsto assist you in completing this lab in Jamovi. Note the different variable icons used in Jamovi to represent different variable levels. These are important since a mean or average, for example, cannot be computed with Nominal Data. Lab Details Your submission for this Lab Assignment should be a Jamovi file with an omv extension. NOTE that you will not be able to Preview your submission since you are only able to see the file when in the Jamovi application. Create a variable called Average Exam Score, the average of exam scores 1, 2, and 3. Use the compute mean command to do this. Transform the Motivation Variable into Motivation Groups with three groups: Low (1-3), Medium (4-6), and High (7-9). Use the layered IF command to do this. Create a frequency table for the residence variable. Use the descriptive statistics function to find the mean and standard deviation of the life satisfaction variable split by two variables; extra-curricular involvement and Motivation_Groups. Report each mean and standard deviation and provide output. Find the mean and standard deviation for exam 1, exam 2, exam 3, and average exam scores variables. Compute histograms with a normal curve (density) for average exam scores and life satisfaction scores. Create a histogram without a normal curve (density) for exams 1, 2, and 3. Split the data by the motivation groups variable and find the mean exam score and life satisfaction score for each group as well as the histogram and density for each group. Important This lab will utilize Jamovi, to review the resources linked in your Course Tools and Resources to get started with Jamovi. Please reach out to your instructor with any questions or concerns. You may find it best to download the software for Jamovi directly to your device for free if you wish. This can be done through the Jamovi webpage.
Description Test specifications provide a descriptive outline of a test and can include information about the construct measured, the format and structure of a test, the number of items, and other information as needed. In this week’s Learning Resources, there is a Test Specification Template that you will complete for your proposed measure. The information in this template will be used in future weeks as well. The template will help guide you through determining the specifications for your test. There is also a completed template that you may look at as a reference. You will need to search the literature for similar constructs to help inform the definition of the construct. Be sure to include both Learning Resources and the resources you found as a result of your search to support the construct definition you provide in the template.
Description Explain the conceptual and quantitative relationships between Alpha risk and Beta risk when testing hypotheses, and include the impact sample size plays in managing these risk levels. This is a double-discussion assignment (80 points) that should be submitted as a Microsoft Word or Adobe Acrobat document submission. There are no responses to other students required (therefore, the assignment will close and lock shortly after the due date and time). Some students have been asking how many words this essay should be. Generally I worry more about quality than quantity, but it's a fair question. It’s a double discussion with no responses required, so… since each discussion would typically be up to 200 words on your initial post, plus another hundred on each response, you would typically be in the 400-500 word range for a solid discussion. Since this is a double, you might best aim for the 800-1000 word range. It’s possible to adequately cover the topic with a bit less, but it would require good solid writing to do so. If you are struggling with what to talk about in this essay, I recommend you re-watch the alpha-and-beta videos in Unit 10. Don't just write a brief blurb about the definitions of alpha and beta error. In particular, you should be writing about the ways that accepting an Alpha risk increase can impact total risk -- this is what we concentrate on as engineers. Hypothesis testing is a statistical technique, but risk management is an engineering requirement. Also consider what happens to these distributions as we increase the sample sizes being analyzed (Hint: What happens to the standard error as n increases?). The distinction between Type I and Type II error -- also know as Alpha and Beta error -- is introduced, with an emphasis on recognizing that different engineering applications will want to optimize a balance between these two types of error differently. It is a common misconception that Type I error should always be minimized. In fact, this approach maximizes Type II error which might be the worst possible thing to do in an engineering design. DISTINGUISHING ALPHA VS. BETA ERROR Alpha error derives directly from the selection of the confidence boundary or interval selected during analysis - it is in the control of the statistician selecting it. Beta error is a result of that Alpha choice PLUS the reality of the true population represented by the sample -- it is unknown, and often unknowable. The Power of our statistical test is a result of the interaction of these two factors. CHANGES TO BETA RISK WITH INCREASING DEVIATION While Alpha risk is known by selection, the actual Beta risk is unknown because we don't know the true population. As the true value deviates from our estimate, the Power of the hypothesis test increases, meaning that the more wrong our estimate is, the more likely our hypothesis test will detect it and reject the Null hypothesis.
Description To prepare for this Assignment: Review the feedback you received from your Instructor on the test specifications for your measure. Using the feedback and what you have learned about test development thus far, make necessary revisions to your construct definition and create 10 to 15 items for your measure. Consider how you would score your measure. For instance, what numbers would you assign to response choices (e.g., strongly disagree = 1, disagree = 2, neutral = 3, agree = 4, strongly agree = 5 or 0 = incorrect and 1 = correct)? Would you compute the sum of the individual item scores to determine a raw total score? Would you reverse score any of the items? Would you weight any of the items more heavily than the others? Submit a paper that includes the following: A complete definition of the construct for your measure, based on feedback you have received in previous weeks. Be sure to include cited evidence from the empirical literature that helped you create an operational definition of this construct. Ten to 15 test items for your measure. Be sure to include the response options you will use, along with your initial thoughts about how the measure will be scored. If your measure has more than one construct (for example, it has five different elements of job satisfaction), 10 to 15 items per construct and a longer submission will be required.
Description The Steps To Take: When you have chosen your NOMINAL variable: Gather the frequency distribution for your variable and be sure you are using the numbers for the 2022 survey year. You will use the frequency distribution to find the mode, when relevant. Remember to ignore any category that is for a "non" answer, e.g., don't know, no answer, no response, etc. Be sure to note the names of the categories - they may be coded with numbers but those do not mean anything - use the names for each category! Analyze only your nominal variable in this part, and discuss it just like we've been doing in the worksheet, homework, and discussion, for central tendency and variability. If you would like more guidance on how to choose and deal with your variables, check out the examples tab. Use the outline to write up your analysis. If you know a formatting style, e.g., MLA or APA or ASA, use it. Type up your paper in whatever program you use for that, e.g., Word, Google Docs, etc.. Save it often if the program doesn't do that for you. (Back up is good!) Look at the rubric and refer to it when you edit your draft - it shows you what is expected in each section (just like the outline!). There is no great need to include the frequency distributions - but if you do want to include them, put them in an appendix (optional). Visit the Writing Center (virtually or in person) with a draft and get their feedback on what can be better. Edit accordingly. After you have submitted and I have reviewed it, please read my comments. Let's talk about how it went. It will be marked complete if you have a paragraph describing your appropriate central tendency and variability statistical patterns for your variable in your own words. If it is marked incomplete and you turned it in on time, we will have time to do a re-submission, if you wish. Use This Outline: Nominal Variable– Describe the distribution of your data for this variable. Interpret the frequency distribution and appropriate measure(s) of central tendency (Mode). Introduction - Tell us what your variable is, in everyday words and, briefly, why you chose it. Discussion - Description of the statistical patterns of central tendency and variability, in everyday words. Use ONLY the relevant statistics for the level of measurement. OPTIONAL - Appendix - frequency distributions and/or the work done to get the the statistics you used in the discussion.
