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Q1:The Microprocessor data shows the demand for one type of chip used in industrial equipment from a small manufacturer. . Construct a chart of the data. What appears to happen when a new chip is introduced? Develop a regression model to forecast demand that includes both time and the introduction of a new chip as explanatory variables. • What would the forecast be for the next month if a new chip is introduced? What would it be if a new chip is not introduced?See Answer
Q2:1. Access 2021, 2020, 2019, and 2018 Intel Forms 10-K from the SEC.gov EDGAR database. Do not use 10Q.See Answer
Q3:2. Using the Form 10-K and annual reports, answer the following questions: (a) Craft a short succinct narrative of Intel's business including what the company does and what are the major product segments. Explain the major product transition taking place at the company. (Hint: this is described in 2019). Do not cut and paste from the annual report, this narrative should be in your own words. Points will be deducted for this. Your source should only include the annual reports. Do not take information from the internet or Wikipedia. The goal here is for you to be able to read and decipher and translate an annual report. This will be a base for you to later assess Intel's competitiveness in their industry. You are limited to three sentences for this description which will require you to be very precise. Points will be deducted for a description with more than three sentences. (15pts) (b) Provide a bar graph of revenue for the past 5 years (ie. 2017-2021) detailed in the financial statements. Overlay the revenue growth rates on your bar graph. Do not cut and paste any graphs from the financial statements. Your graph should be visually clear and appealing and accurate. Include proper labels and title. You should have a label on each data point. Points will be deducted for improper labeling. (20pts) (c) Explain how and when revenues are recognized? (Hint: Notes to Financial Statement) Provide details (ie. Not just accrual accounting). Discuss the accounting change made in 2018 and how that would affect the revenues reported in 2018. Focus on top-line sales only. No need for a detailed description of rebates, etc. (15pts)See Answer
Q4:It will be helpful to know the following terms and their basic meaning. Chips/semiconductor Nanometer (nm) Wafer CPU GPU 5GSee Answer
Q5:5-14 The Southern Rail Company ships coal by rail from three coal mines to meet the demand requirements of four coal depots. The following table shows the distances from the mines to the various depots and the availabilities and requirements for coal. Determine the best shipment of coal cars to minimize the total miles traveled by the cars. Table for Problem 5-14 From Parris Butler Century Demand for cars To Columbia Albany Springfield Pleasatanburg Supply of Cars 50 20 100 30 30 80 40 45 60 10 80 25 70 90 30 20 35 60 25See Answer
Q6:A meat packing house is creating a new variety of hot dog for the low-calorie, low- fat, low-cholesterol market. This new hot dog will be made of beef and pork, plus either chicken, turkey, or both. It will be marketed as a 2-ounce all-meat hot dog, with no fillers. Also, it will have no more than 6 grams of fat, no more than 27 grams of cholesterol, and no more than 100 calories. The cost per pound for beef, pork, chicken, and turkey, plus their calorie, fat, and cholesterol counts are shown in the following table. Cost/Pound Beef Pork $0.76 Turkey $0.82 Chicken $0.64 $0.58 Calories/Pound 640 1,055 780 528 Fat (g/lb.) Cholesterol (g/lb.) 32.5 54.0 25.6 6.4 210 205 220 172 The packer would like each 2-ounce hot dog to be at least 25% beef and at least 25% pork. What is the most economical combination of the four meats to make this hot dog?See Answer
Q7:2. A certain brand of flood lamps has a lifetime that is normally distributed with a mean of 3,750 hours and a standard deviation of 300 hours. a. What proportion of these lamps will last for more than 4,000 hours? b. What proportion of these Lams will last less than 3,600 hours? c. What proportion of these lamps will last between 3,800 and 4,100 hours? (6 marks) d. What lifetime should the manufacturer advertise for these lamps in order that only 2% of the lamps will burn out before the advertised lifetime? (6 marks) Effective date 06/09/2019 (5 marks) (5 marks) Page 1 of 4See Answer
Q8:3. The amount of time spent by American adults playing sports per week is normally distributed with a mean of 4 hours and standard deviation of 1.25 hours. a. Find the probability that a randomly selected American adult plays sports for more than 5 hours per week. (4 marks) b. Find the probability that if four American adults are randomly selected, their average number of hours spent playing sports is more than 5 hours per week. (6 marks) c. Find the probability that if four American adults are randomly selected, all four play sports for more than 5 hours per week. (6 marks)See Answer
Q9:Problem 3 There is an opportunity to acquire well-servicing equipment for $600,000. There is a 15 % probability that after acquiring the equipment we decide to NOT pursue the well-servicing business. In this case, we could sell the equipment next year for $500,000. If we go into the well- servicing business, we anticipate annual after-tax revenues of $300,000 for 5 years, starting next year. There is a 35 % probability that we enter the business and have to overhaul and upgrade some of the equipment in 2 years. This would reduce after-tax cash flow by $200,000 in Year 2. Should we purchase the equipment? We are currently earning 20% on other investment opportunities.See Answer
Q10:Problems 3-17 Kenneth Brown is the principal owner of Brown Oil, Inc. After quitting his university teaching job, Ken has been able to increase his annual salary by a fac- tor of over 100. At the present time, Ken is forced to consider purchasing some more equipment for Brown Oil because of competition. His alternatives are shown in the following table: EQUIPMENT Sub 100 Oiler J Texan FAVORABLE UNFAVORABLE MARKET MARKET ($) ($) 300,000 -200,000 250,000 -100,000 75,000 -18,000 For example, if Ken purchases a Sub 100 and if there is a favorable market, he will realize a profit of $300,000. On the other hand, if the market is unfa- vorable, Ken will suffer a loss of $200,000. But Ken has always been a very optimistic decision maker. (a) What type of decision is Ken facing? (b) What decision criterion should he use? (c) What alternative is best? 31%See Answer
Q11:KID ing Wallace Garden Supply is more accurate. :5-17 Data collected on the yearly demand for 50-pound bags of fertilizer at Wallace Garden Supply are shown in the following table. Develop a 3-year mov- ing average to forecast sales. Then estimate demand again with a weighted moving average in which sales in the most recent year are given a weight of 2 and sales in the other 2 years are each given a weight of 1. Which method do you think is better? YEAR 1 2 3 4 5 6 7 DEMAND FOR FERTILIZER (1,000s OF BAGS) 4 6 4 5 10 8 7 (Continued on next page)/nYEAR 8 9 10 11 DEMAND FOR FERTILIZER (1,000s OF BAGS) 9 12 14 15 OIXSee Answer
Q12:Q1. Summary Information and Basic Counts a) How many different store units does Mr. Macky's currently have? b) How many different large market store units does Mr. Macky's currently have? c) How many different medium market store units does Mr. Macky's currently have?See Answer
Q13:Q3. Headcount a) Fill in the table below for the current employees in Mr. Macky's. Job Titles Number of Females Number of URM* Assistant Manager Manager Non-Exempt Employees (All) b) Fill in appropriate data for each date # Hired On or Before Date and Date January 1, 2020 December 31, 2020 January 1, 2021 December 31, 2021 January 1, 2022 December 31, 2022 Average Still Employed # Hired On or Before Date but Terminated on or after specified date Year 2020 2021 2022 # Employed on Specified Date Year 2020 2021 2022 Number of those in Age 40 or older # Hired on that Specific Day c) Using the information from the table above, what is the average headcount in each year? Average Headcount Terminated on Specific Date d) What is the average number of employees (i.e., headcount) per store unit for each year? Medium Market Large MarketSee Answer
Q14:Q4. Turnover a) Using the Past and Current Employees tab, summarize the nature and total amount of turnover in each of the following years: Year 2020 2021 2022 b) What is the overall turnover rate in each year? Unit # 20 40 60 80 100 120 140 Discharged Number of Individuals Employed on January 1, 2022 Year 2020 2021 2022 c) Report the requested information, ultimately so that you can compute the unit turnover rate in 2022, for the stores listed below. Quit Number of Individuals Employed on December 31, 2022 Turnover Rate Total Number Who Left the Company Average 2022 Headcount Number of people who left unit in 2022 (i.e., turnover count) Unit Turnover Rate/nSee Answer
Q15:Q5. Tenure a) Look at current employees. What is the average tenure of the following employees? Employee Group Average Tenure (in years) (Use two decimal places) All employees Assistant Managers Managers b) Which store unit has the highest average tenure in 2022? Unit # Average tenure in this unit in 2022: c) Which store unit has the low est average tenure in 2022? Unit # Average tenure in this unit in 2022:See Answer
Q16:Q6. Summary Information: Manager's Pay and Performance a) Provide the descriptive statistics for wages of currently employed managers and assistant managers in 2022. Managers' Wage Job Title Mean Standard Deviation Range Minimum Maximum Number of Observations b) For the previous three years, what are the means and standard deviations of wage rate and performance rating scores for ALL (both employed and no-longer employed) managers and assistant managers? (Note that Assistant Managers can be promoted to Managers, so make sure you are using the right job title in the right year.) Wage Rate (S) Performance Rating* Job Title Year Mean Assistant 2020 Manager 2021 2022 Manager 2020 2021 Assistant Managers' Wage 2022 Standard Deviation Mean Standard DeviationSee Answer
Q17:Q1. Analyzing the Performance Data of Mr. Macky's. Compute the correlation for all years of data (so, include all data from 2016 to 2022) Number of observations on which your analyses are based: i. ii. Fill in the correlations in the table Performance Rating (Manager) 1 Manager's Performance Rating Scores Assistant Manager's Performance Rating (or average of ratings) Store Market (1-Large, 0-Medium) Unit Sales r= r= r= Performance Rating (Asst. Manager) r= r= 1 Store Market Unit Sales (1=Large) r= 1 1/nX= Performance Rating of Managers (2022) Number of Observations in Regression Model 1: d) Regression Model 2 Y=Unit sales (2022) X= Performance Rating of Assistant Managers (2022) Number of Observations in Regression Model 2: e) Regression Model 3 Y=Unit sales (2022) X1= Performance Rating of Managers (2022) X2= Performance Rating of Assistant Managers (2022) f) Regression Model 4 Y=Unit sales (2022) Coefficients Number of Observations in Regression Model 3: X1= Performance Rating of Managers (2022) X2= Store Market Coefficients g) Regression Model 5 Y=Unit sales (2022) Coefficients Number of Observations in Regression Model 4: Coefficients (Use 4 Decimal Places) P-value (Use 4 Decimal Places) P-value (Use 4 Decimal Places) P-value (Use 4 Decimal Places) P-value Module 2 Answers: Page 9 (p<.05) (Yes or No) Significant Effect? (p<.05) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No) Significant Effect? (p<.05)/nX1= Performance Rating of Assistant Managers (2022) X2= Store Market Number of Observations in Regression Model 5: h) Regression Model 6 Y=Unit sales (2022) X1= Performance Rating of Managers (2022) X2= Performance Rating of Assistant Managers (2022) X3= Store Market Number of Observations in Regression Model 6: i) Regression Model 7 Y=Unit sales (all years) Coefficients j) Regression Model 8 Y=Unit sales (all years) Coefficients X1= Performance Rating of Managers (all years) X2= Store Market Number of Observations in Regression Model 7: Coefficients X1= Performance Rating of Assistant Managers (all years) X2= Store Market Number of Observations in Regression Model 8: (Use Decimal Places) P-value (Use 4 Decimal Places) P-value (Use 4 Decimal Places) P-value (Use 4 Decimal Places) Module 2 Answers: Page 10 (Yes or No) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No)/nk) Regression Model 9 Y=Unit sales (all years) X1= Performance Rating of Managers (all years) X2= Performance Rating of Assistant Managers (all years) X3= Store Market Number of Observations in Regression Model 9: 1) Regression Model 10 Y=One-Year Change in Unit sales (for all possible years) Xl-Performance Rating of Managers X2= Performance Rating of Assistant Managers X3= Store Market m) Regression Model 11 Y=Unit sales (all years except 2016) Coefficients Number of Observations in Regression Model 10: X1= Performance Rating of Managers X2= Performance Rating of Assistant Managers X3= Store Market X4=Prior Unit sales (from prior year) Coefficients Coefficients Number of Observations in Regression Model 11: P-value (Use 4 Decimal Places) P-value (Use 4 Decimal Places) P-value (Use 4 Decimal Places) Module 2 Answers: Page 12 Significant Effect? (p<.05) (Yes or No) (Yes or No) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No) (Yes or No) (Yes or No)/nn) To answer this question, (1) identify which model (preferably one model, but few more are okay if you want to make any comparison) you will bring and present to the Head of HR Analytics, (2) briefly interpret your finding(s) and takeaway(s) from the model you picked, and (3) justify why you think it is better than any other regression models. Please concisely make your point in a plain language for the Head of HR department using no more than 200 words at maximum. Answer:See Answer
Q18:Q3. Computing SDy based on Performance Rating and Unit Performance a) Using the standardized scores of performance ratings for managers and assistant managers, compute SDy by running regressions on the unit sales of the same years. Y=Unit sales (all years) Significant Effect? (p<.05) X1=Standardized Performance Rating of Managers X2= Standardized Performance Rating of Assistant Managers Number of Observations in Regression Model: b) SDy of Managers = $_ c) SDy of Assistant Managers = $_ Y=One-Year Change in Unit sales (for all years possible) Coefficients X1=Standardized Performance Rating of Managers X2= Standardized Performance Rating of Asst. Managers d) Repeat Question 3a and compute SDy for managers and assistant managers yet by regressing one-year change in unit sales rather than the unit sales of concurrent years. Fill in the table below and blanks for SDy. Coefficients P-value (Use 4 Decimal Places) Number of Observations in Regression Model: e) SDy of Managers = $_ f) SDy of Assistant Managers = $_ (Yes or No) P-value (Use 4 Decimal Places) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No)/ng) Repeat Question 3a and compute SDy for managers and assistant managers yet after controlling for one-year prior unit sales and store market information. Fill in the table below and blanks for SDy. Y=Unit sales (for all possible years except 2016) X1= Standardized Performance Rating of Managers X2= Standardized Performance Rating of Asst. Managers X3= Store Market X4=Prior unit sales (one-year) Coefficients Number of Observations in Regression Model: h) SDy of Managers = $_ i) SDy of Assistant Managers = $_ P-value (Use 4 Decimal Places) Significant Effect? (p<.05) (Yes or No) (Yes or No) (Yes or No) (Yes or No) ₁) Compare the SDy's that you have computed above. Among them, (1) which SDy do you think provides the most precise estimate? (2) why? "I think the best estimates of SDy for managers and assistant managers are from (please check): I Question 3a Question 3d Question 3g k) "I have chosen the SDy above because..." (briefly state with 100 words maximum):See Answer
Q19:Q4. The Relationship between Unit Turnover and Performance over time a) Compute a correlation between the unit turnover rate of 2021 and 2022. b) Regression Model 1 Y=Unit sales (2022) X= Unit Turnover Rate (2022) Number of Observations in Regression Model 1: c) Regression Model 2 Y-Unit sales (2022) X1=Unit Turnover Rate (2022) X2= Unit Prior Sales (2021) Coefficients d) Regression Model 3 Number of Observations in Regression Model 2: Y=Change in Unit sales (2021-2022) X= Unit Turnover Rate (2022) Coefficients Coefficients Number of Observations in Regression Model 3: P-value (Use 4 Decimal Places) P-value (in 4 Decimal Places) P-value (Use 4 Decimal Places) Significant Effect? (p<.05) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No) Significant Effect? (p<.05) (Yes or No)/ne) Regression Model 4 Y=Change in Unit sales (2021-2022) X= Change in Unit Turnover Rate (2022 rate-2021 rate) Number of Observations in Regression Model 4: Regression Model 5 Y= Unit sales (2022) Coefficients Xl=Change in Unit Turnover Rate (2022 rate-2021 rate) X2= Prior Unit Sales (2021) Coefficients Number of Observations in Regression Model 5: P-value (Use 4 Decimal Places) P-value (in 4 Decimal Places) Significant Effect? (p<.05) (Yes or No) Significant Effect? (p<.05) (Yes or No) (Yes or No) g) Considering the five regression models you conducted in Question 4b through Question 4f, briefly interpret the results of regression models in a plain language, explaining the nature of relationships between unit sales and turnover at a given year and over years. Is there any interesting finding here for Mr. Macky's management? Answer:/nQ5. Computing the percent of unit-level variance of Employee Engagement Data a) Compute the following for each of the nine items of employee engagement survey. Item Total variance Variance of group averages Percent of variance attributable to group membership Job Satisfaction Collaboration Communication Support Customer Focus Personal Growth Inclusion Empowerment Accountability b) Percent of variance attributable to group membership: c) Based on your findings in Question 5a and Question 5b above, which individual-level engagement items can be also considered for aggregated effect at the unit level on other unit-level? Would it be appropriate to aggregate the overall measure of employee engagement? Answer:See Answer
Q20:Q6. Employee Engagement, Turnover and Unit Performance Over Time a) Prepare the data for and conduct a multiple regression analysis. Y = Unit sales (2022) Coefficients X1 = Average Unit Engagement Rating from 2022 Raw Engagement Data Subset (Average of the nine items) X2 = Unit Turnover Rates (2022) X3 = Prior Unit Sales (2021) Number of Observations in Regression Model: X1 = Average Unit Engagement Rating for Non-Exempt Employees from Engagement Survey Results (Average of then nine items) X2 = Unit Turnover Rates (2022) X3 = Prior Unit Sales (2021) P-value (Use 4 Decimal Places) b) Correlation between your computed unit-level average engagement score, and the value provided for Non-Exempt employees by unit for 2022. r= Number of Observations in Regression Model: c) Conduct the same regression as for Question 6a, but now use the average non-exempt score from the Engagement Survey Results tab. Y = Unit sales (2022) Coefficients Significant Effect? P-value (Use 4 Decimal Places) (p<.05) (Yes or No) (Yes or No) (Yes or No) Significant Effect? (p<.05) (Yes or No) d) Compare these two regressions. Which one do you think is better? Why? (Yes or No) (Yes or No)See Answer

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