5-3 Assignment - Means, Test of Hypothesis

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More real estate Consider the Albuquerque home sales from Exercise 29 again. The regression analysis gives the model Price = 47.82 + 0.061 Size. a) Explain what the slope of the line says about housing prices and house size. b) What price would you predict for a 3000-square-foot house in this market? c) A real estate agent shows a potential buyer a 1200-square- foot home, saying that the asking price is $6000 less than what one would expect to pay for a house of this size. What is the asking price, and what is the $6000 called?

Assume there are 3,600 cases in the validation dataset, and 12% of these cases have a value of 1 for churn (the primary/positive event). Questions a) to c) are based on data for the 3,600 cases (see table below). Depth (% Contacted) Model Cumulative Gain Cumulative Lift Decision Tree 34.42 6.84 Logistic Regression Neural Network 20.19 4.01 34.62 6.88 Decision Tree Logistic Regression Neural Network 10 64.90 6.06 10 36.06 3.15 10 62.50 5.54 Decision Tree 15 73.96 1.82 Logistic Regression Neural Network 15 49.04 2.62 15 82.21 3.97 Decision Tree Logistic Regression 20 78.39 0.87 20 59.13 2.01 Neural Network 20 86.54 0.86 a) Which model has the highest Cumulative Lift at a depth of 20%? What is the lift? b) If the Cumulative Gain at a depth of 10% for the Decision Tree is converted to number of primary/positive event cases, what will be the number of cases? Show your calculation. c) If the Cumulative Gain at a depth of 15% for the Neural Network model is converted to number of…

What is the F- test statistic and p-value

Find out coefficient of Variation (CV). Note: Use MS-EXCEL for the Calculation, Take Snapshot after analysis

The production department is proposing the purchase of an automatic insertion machine. It has identified three machines and has asked the accountant to analyze them to determine which one has the best average rate of return. Machine A Machine B $45,730.58 $60,103.80 326,647.00 200,346.00 Ca, Machines B and C have the same preferred average rate of return b. Machine C C. Machine 11 d. Machine A Estimated average income Average investment Machine C $74,639.55 497,597.00

Newport, Inc. used Excel to run a least-squares regression analysis, which resulted in the following output: Regression Statistics Multiple R R Square Observations 0.7225 0.8500 30 Coefficients Standard Error T Stat P-Value 0.021 Intercept Production (X) 31,000 5.87 3,493 2.86 0.4640 14.30 0.000 a. What is Newport's total fixed cost? Total Fixed Cost b. What is Newport's variable cost per unit? (Round your intermediate calculations to 2 decimal places.) Variable Cost per unit c. What total cost would Newport predict for a month in which they sold 5,000 units? Total Costs d. What proportion of variation in Newport's cost is explained by variation in production? (Round your intermediate calculations to 2 decimal places.) Proportion of Variation

For the Housing data sheet, Compute the following for the Price column – NE Sector = ‘Yes’, NE Sector = ‘No’ and Overall. You are free to use either Excel functions or the tools available in the Analysis Toolpak. (a) Mean      (b) Median      (c) Standard Deviation      (d) Variance    (e) 4 Quartiles     (f) Range     (g) IQR

For the Housing data sheet, Compute the following for the Price column – NE Sector = ‘Yes’, NE Sector = ‘No’ and Overall. You are free to use either Excel functions or the tools available in the Analysis Toolpak.(a) Mean(b) Median(c) Standard Deviation(d) Variance(e) 4 Quartiles(f) Range(g) IQR Using the following:

SHOW YOUR WORK IN THE SPACES PROVIDED BELOW FOR FULL CREDIT. Properties of Normal Distribution: (3p) Write the word or phrase that best completes each statement or answers the question.  a. What is the total area under the normal curve?    b. The normal distribution is defined by two parameters. What are they?   c. What are the mean and standard deviation of the standard normal distribution?

Quest. Simulation) The mai..gement of Brinkley Corporation is interested in using simulation to estimate the profit per unit for a new product. Probability distributions for the purchase cost, the labor cost, and the transportation cost are as follows: Labour Purchase Transportation Cost ($) Cost Cost ($) Probability ($) Probability Probability 10 0.25 20 0.1 3 0.75 11 0.45 22 0.25 0.25 12 0.3 24 0.35 25 0.3 Assume that these are the only costs and that the selling price for the product will be $45 per unit. a. Provide the base (most likely)-case, worst-case, and best-case calculations for the profit per unit. b. Set up intervals of random numbers that can be used to randomly generate the three cost components, and find the average profit based on 10 simulation trials. Show your simulation model (including the formulas sed) as developed with Excel. c. Using the random numbers 0.3726, 0.5839, and 0.8275, calculate the profit per unit. ( d. Management believes the project may not be…

Using the accompanying Home Market Value data, develop a multiple linear regression model for estimating the market value as a function of both the age and size of the house. State the model and explain R Click the icon to view the Home Market Value data. State the model for predicting MarketValue as a function of Age and Size, where Age is the age of the house, and Size is the size of the house in square feet. MarketValue = +Age+ (Size (Type integers or decimals rounded to three decimal places as needed.) The value of R2,, indicates that % of the variation in the (Type integers or decimals rounded to three decimal places as needed.) is explained by

In creating the T2 measure one mixes P* and T-bills to match the _____ of the market and in creating the M2 measure one mixes P* and T-bills to match the _____ of the market.    Group of answer choices   beta, alpha alpha, beta standard deviation, beta beta, standard deviation

I need help with this worksheet that calculates whether or not leasing or purchasing a vehicle is a better option. I have attached a sample from our reading along with a screenshot of the spreadsheet that we are to work on. Can I get an explanation for how this is calculated?

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Consider the following data for a dependent variable y and two independent variables, x1 and 12. 30 12 94 47 10 109 25 18 112 51 16 178 40 94 51 19 175 75 171 36 12 118 59 13 143 77 17 212 Round your all answers to two decimal places. Enter negative values as negative numbers, if necessary. a. Develop an estimated regression equation relating Y to ¤1. Predict y if æ1 = 35. b. Develop an estimated regression equation relating y to x2. ŷ = + Predict y if x2 = 25. ŷ = c. Develop an estimated regression equation relating y to ¤1 and 2. Predict y if x1 = 35 and x2 = 25. ŷ =

Please answer with reason for all why the option is correct and why the other options are incorrect

A prospective MBA student would like to examine the factors that impact starting salary upon graduation and decides to develop a model that uses program per-year tuition as a predictor of starting salary. Data were collected for 37 full-time MBA programs offered at private universities. The data are stored in the accompanying table. The least-squares regression equation for these data is Y₁ = - 13,863.426 +2.437X, and the standard error of the estimate is Syx = 15,910.578. Assume that the straight-line model is appropriate and there are no serious violations the assumptions of the least-squares regression model. Complete parts (a) and (b) below Click the icon to view the data on program per-year tuition and mean starting salary a. At the 0.01 level of significance, is there evidence of a linear relationship between the starting salary upon graduation and program per-year tuition? Determine the hypotheses for the test. Ho B₁ = D H₁ P₁ #0 (Type integers or decimals. Do not round.)…

A market research survey is available for 3000 JD. Using a decision tree analysis, it is found that the expected monetary value with no survey is 36,000 JD. If the expected value of sample information is 3,000 JD, what is the expected value with the survey? a. 39,000 JD b. 27000 JD c. 37000 d. 36,000 JD e. 33,000

Consider the following set of dependent and independent variables. Complete parts a through c below. y 9 11 D 15 15 21 24 28 32 X1 2 6 6 8 6 11 15 20 X2 16 10 14 11 3 8 7 4 a. Using technology, construct a regression model using both independent variables. y= (15.3952) + (1.0092) x₁ + (-0.5869)x2 (Round to four decimal places as needed.) b. Test the significance of each independent variable using α = 0.05. Test the significance of x₁. Identify the null and alternative hypotheses. Ho B₁ = H₁ B₁ 0 0 (Type integers or decimals.) Calculate the appropriate test statistic. The test statistic is 4.20 (Round to two decimal places as needed.) Determine the appropriate critical value(s) for α = 0.05. The critical value(s) is (are) ☐ (Round to two decimal places as needed. Use a comma to separate answers as needed.)

Compute mean .  Note: Use MS-EXCEL for the Calculation, Take Snapshot after analysis