assignment 6a

Question 3 An organization uses a business intelligence system to predict products that tend to be purchased together. This is an example of. O A) Regression Analysis B) Cluster Analysis C) REM Analysis D) Market Basket Analysis

q10-  What is the best description of Granger-causality? Select one: a.   the ability of lags of one variable to contribute to the forecast of another variable   b. the ability of a variable to predict its own future c. the ability of the one variable to explain it own past d. None of the above Clear my choice

Part B?

A marketing analyst wants to examine the relationship between sales (in $1,000s) and advertising (in $100s) for firms in the food and beverage Industry and collects monthly data for 25 firms. He estimates the model Sales-o Advertising. The following ANOVA table shows a portion of the regression results. Regression Residual df 1 23 55 78.53 504.02 MS 78.53 21.91 T 3.58

Descriptive Statistics Analysis Results Current Battery.                          Proposed Battery Mean 598.7             Mean 697 Standard error 7.816009212.     Standard error 3.431876714 Median 602.                          Median 700 Mode 620.                                  Mode 710 Standard deviation 24.71639132.    Standard deviation 10.85254706 Sample variance 610.9        Sample variance 117.7777778 Range 86.                      Range 31 Minimum 534.                 Minimum 679 Maximum 620.                   Maximum 710 Sum 5,987                               Sum 6,970 Count 10 g.                            Count 10 *Battery time between charges shown in minutes Create a 1 slide infograph

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2:56 +973 3686 6592 06/01/2022, 2:44 PM QUESTION 14 The holder of Cypres Recordings studied the relationship among sales (y) and the amount spent on advertising (x). A random sample of 38 recordings gives the following information The intercept = 18.47 and the slope0 98 The estimated sales for 18 amount of advertisement is equal to? (Round answer to three decimal places ex. 2.091)

The classified department of a monthly magazine has used a combination of quantitative and qualitative methods to forecast sales of advertising space. Results over a 20-month period are as follows: Month Error Month Error 1 —8 11 1 2 —2 12 6 3 4 13   4 7 14 4 5 9 15 1 6 5 16 —2 7 0 17 —4 8 —3 18 —8 9 -9 19 —5 10 —4 20 —1 a. Compute a tracking signal for months 11 through 20. Compute

Student Performance Results Pre- Post- Pre- Post- Student ID LG1 (%) LG1 (%) LG2 (%) LG2 (%) Pre- Assessment Assessment Assessment Assessment Assessment Assessment LG3 (%) 1 70 85 75 80 90 80 098 Post- LG3 (%) 85 2 75 90 90 80 85 75 90 96 3 80 85 75 1 90 70 85 4 75 90 70 85 75 00 90 5 70 85 75 90 90 6 75 50 00 80 95 85 90 80 85 75 90 7 80 85 75 90 90 70 85 8 75 90 70 85 75 90 9 70 85 75 90 80 85 10 ° 75 55 90 80 85 75 90 11 80 85 75 90 00 12 75 90 20 70 70 85 85 75 90 13 70 85 75 90 80 85 55 14 75 90 80 85 75 90 15 80 85 75 90 70 85 16 75 90 70 85 75 90 17 70 85 75 90 80 85

Forecasting on Operation Management

a. 15.64 b. 16.54 c. 14.56 d. 56.14

q1- In order to determine the opinions and attitudes of customers who regularly shop at a particular centre, an analyst stands outside a large department store in the centre and randomly selects people to participate in the survey. Briefly explain why the analyst uses a random sample rather than the population to investigate the question of interest. (Hint: List two main reasons and briefly explain each.)

. Prepare a scatter diagram for each of these data sets and then express in words the apparent relationship between the two variables. Put the first variable on the horizontal axis and the secondvariable on the vertical axis.b. Temperature (°F) 65 63 72 66 82 58 75 86 77 65 79Error rate 1 2 0 0 3 3 1 5 2 1 3

1- Explain the facts regarding the data, including number of variables and datapoints.   #of variables       # of observations     2- Complete the table as follows, List the variables features including, names, variable, level, etc.    Variable Variable Type Variable Level     Age Numeric Ratio     Gender Categorical        Sales_Rep         Business         Years         College         Personality         Certificates         Feedback         Salary         NPS       Part 3 is shown on the photo

Q1) Forecasting is both art and science. Describe the situations where we use Qualitative forecasting techniques and quantitative forecasting techniques

Month Actual Sales Naive Forecast- Absolute Value of (# of Product X) Sales Errors (# of Product X) Jan/19 Feb/19 Mar/19 Apr/19 May/19 Jun/19 Jul/19 Aug/19 Sep/19 Oct/19 Nov/19 Dec/19 Jan/20 1,860 2,033 3,556 4,211 6,250 7,990 10,250 9,850 9,980 9,990 7,895 5,353 - Explain the calculation method for the Naive Forecast model. the faln

Solved the problema) Use a 3-year moving average to forecast the sales ofVolkswagen Beetles in Nevada through year 6.b) What is the MAD? ~c) What is the MSE?

Do it accurate clean handwriting dont use chat gpt etc solve accurate

Develop Linear Regression Model. Forecast sales for 8, 14 and 17 years of education. Sales(1000s)                   Years of Education 24                                          10 18                                          9 20                                          11 22                                           6 26                                          13 23                                          16 21                                          18

1- Explain the facts regarding the data, including number of variables and datapoints.   #of variables       # of observations     2- Complete the table as follows, List the variables features including, names, variable, level, etc.    Variable Variable Type Variable Level     Age Numeric Ratio     Gender Categorical        Sales_Rep         Business         Years         College         Personality         Certificates         Feedback         Salary         NPS

Make a scatter plot of the data and determine which type of model best fits the data.     linear     quadratic     exponential     square root

ic 2-Time Series Analysis and F eBook Problem 6-21 (Algorithmic) The Centers for Disease Control and Prevention Office on Smoking and Health (OSH) is the lead federal agency responsible for comprehensive tobacco prevention and control. OSH was established in 1965 to reduce the death and disease caused by tobacco use and exposure to secondhand smoke. One of the many responsibilities of the OSH is to collect data on tobacco use. The following data show the percentage of U.S. adults who were users of tobacco for a recent 11-year period (http://www.cdc.gov/tobacco/data_statistics/tables/trends/cig_smoking/index.htm). Year 1 2 3 4 5 6 7 8 9 10 11 Percentage of Adults Who Smoke 22.9 25 Peremt of Adults Who St 20 15 21.5 20 8 20.8 a. Choose the correct time series plot. (0) 10 20.1 20.1 18.0 18.9 19.4 19,4 20.3 20.3 20.3 19.4 18.8 4 Year (0) $ 10 12 (1) Percent of Adults Who Smoke 25 20 15 10 Year (0) S 10 12 4

Q5) Monthly sales for a six month period are as follows:  Month SalesJan 18,000Feb 22,000Mar 16,000Apr 18,000May 20,000June 24,000 Compute the sales forecast for July using the following approaches: (1) Four-month moving average; (2) Weighted three-month moving average using .50 for June, .30 for May and .20 for April;(3) Exponential smoothing with α (smoothing constant) equal to .40, assuming a February forecast of 18,000

1Explain with examples what is meant by seasonal variation.

45 A forecasting method has produced the following over the past five months. What is the mean absolute deviation?   Actual Forecast Error |Error| 10 11 -1 1 8 10 -2 2 10 8  2 2 6 6  0 0 9 8  1 1   Select one: a. -0.2 b. 1.2 c. 8.6 d. -1.0 e. 0.0

On February 12 Peg Jones, vice president for operations and maintenance, called into Stephen’s office and asked to study the issue. Specially, Stephen wanted to know whether the average fleet age was correlated to direct airframe maintenance costs, and whether there was a relationship between average fleet age and direct engine maintenance costs. Peg was to report back by February 26 with the answer, along with quantitative and graphical descriptions of the relationship. Peg’s first step was to have her staff construct the average age of Northern and Southeast B727-300 fleets, by quarter, since the introduction of that aircraft to service by each airline in late 1993 and 1994. The average age of each fleet was calculated by first multiplying the total number of calendar days each aircraft had been in service at the pertinent point in time by the average daily utilization of the respective fleet to total fleet hours flown. The total fleet hours was then dividend by the number of…