5-3 Assignment - Means, Test of Hypothesis

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

You must use Excel to perform the regression analysis. Provide the answers under the space provided for each question. You must provide the Excel output for the question along with the answers. Round off the values on the output to three-five decimal places if appropriate.Conduct a simple linear regression analysis for each independent variable associated with the external factors, using house price as the dependent variable. Make sure to use the indicator variables for the categorical data. (Significance level of α = 0.05). For each regression:22) Report the p-value of the independent variable and indicate whether it is a significant predictor of house price (based on the p-value being less than 0.05). (4p)23) Report the explained variability (R-squared value) for each variable, whether it is significant based on the p-value. (4p)24) Identify and list any variables that are not significant predictors of house price (i.e., those with p-values greater than 0.05). (2p)Conduct a multiple…

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if you could help me out with 5-a - 6 id really appreciate it

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 =

answer the blank part please ASAP

What is answer for question b)

Least-Squares Regression Method; Scattergraph; Cost Behavior Professor John Morton has just been appointed chairperson of the Finance Department at Westland University. In reviewing the department’s cost records. Professor Morton has found the following total cost associated with Finance 101 over the last five terms: Professor Morton knows that there are some variable costs, such as amounts paid to graduate assistants, associated with the course. He would like to have the variable and fixed costs separated for planning purposes. Required: 1. Prepare a scattergraph plot. (Plot total cost on the vertical axis and number of sections offered on the horizontal axis.) 2. Using the least-squares regression method, estimate the variable cost per section and the total fixed cost per term for Finance 101. Express these estimates in the form Y = a + bX. 3. Assume that because of the small number of sections offered during the Winter Term this year. Professor Morton will have to offer eight…

Which ones are quantitative variables? Motel ID Indoor pool Competitor rooms Office space Distance to competitor Median income Distance to downtown Operating Margin 1 Yes 3478 560 0.1 57 12.9 50.3% 2 No 2967 529 1.4 55.5 0.4 44.6% 3 No 2613 249 1.8 61.5 11.7 43.3% 4 No 3222 425 1.1 51 2.7 43.6%

Using the accompanying data of a TV viewing survey, conduct a hypothesis test to determine if married individuals watch less TV than single individuals. Assume that the population variances are unequal. Click the icon to view the TV viewing survey Is there sufficient evidence at the 0.05 level of significance that the married individuals watch less TV than single individuals? Determine the null hypothesis, H. and the alternative hypothesis. H, Let married people be population 1 and singles be population 2. H₂ 1-1 0 AP 0 (Type integers or decimals. Do not round.) Survey data Compute the test statistic. (Round to two decimal places as needed.) Marital Status Hrs of TV viewing per week Marital Status Hrs of TV viewing per week Married 6 Single 38 Married 17 Single 18 Mamed 13 Single 14 Mamed 21 Single 10 Married 11 Single 14 Married 14 Single 10 Married 15 Single 35 Married 7 Single 20 Married 18 Single Married 28 Single Single 13 Single 18 Single 10 Single 15 Single 14 - X

In a simple linear regression based on 20 observations, it is found b1 = 3.05 and se(b1) = 1.30. Consider the hypothesis : H0 : β1 = 0 and HA : β1 ≠ 0 . Calculate the value of the test statistic.