Which interval level input variables lowers the odds of churning with each unit increase in the variable? Out of these variable, which one lowers the odds of churning the most? Show the calculation of the odds for this one variable. Questions a) to e) are based on the results of the Coefficients and Statistics table from a LogisticRegression Learner node (shown below):Row IDRow 1Row 2Row 3Row4RowSRow6Row7RowBRow9Row 10Row 11Row 12Row 13Row 14Row 15Row 16Row 17Row 18Row 19Row 20Row 21Row 22Row 23Row 24Row 25Row 26Row 27Row 28Row 29Row 30Row 31S LogitYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesYesS Variablegender-MaleSenior Citizen-1Partner-NoDependents YestenurePhoneService-YesMultiplelines-NoMultiplelines YesInternetService-Fiber opticInternet Service-NoOnlineSecurity YesOnlineSecurity-No internet serviceOnlineBackup-NoOnlineBackup-No internet serviceDeviceProtection=YesDeviceProtection-No internet serviceTechSupport YesTechSupport-No internet serviceStreamingTV-YesStreamingTV-No internet serviceStreamingMovies YesStreamingMovies-No internet serviceContract-One yearContract-Two yearPaperlessBiling-NoPayment Method-Mailed checkPayment Method-Bank transfer (automatic)Payment Method-Credit card (automatic)MonthlyChargesTotalChargesConstantD Coeff.-0.0040.310.036-0.078-0.0570.178-0.0870.2651.478-0.214-0.348-0.2140.099-0.2140.11-0.214-0.212-0.2140.503-0.2140.556-0.214-0.659-1.259-0.393-0.331-0.301-0.525-0.03101.383

Given Information: Consider the given results of the coefficients and statistics table from logistic…

Which interval level input variables lowers the odds of churning with each unit increase in the variable? Out of these variable, which one lowers the odds of churning the most? Show the calculation of the odds for this one variable.

Which interval level input variables lowers the odds of churning with each unit increase in the variable? Out of these variable, which one lowers the odds of churning the most? Show the calculation of the odds for this one variable.

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

See similar textbooks

Similar questions

The following data show Transportation Budget for North Carolina (Let year 1- 2003)Year = 2003 Budget (in millions) = 385Year = 2004 Budget (in millions) = 397Year = 2005 Budget (in millions) = 452Year = 2006 Budget (in millions) = 501Year = 2007 Budget (in millions) = 446Year = 2008 Budget (in millions) = 450Year = 2009 Budget (in millions) = 593Year = 2010 Budget (in millions) = 654Year = 2011 Budget (in millions) = 846Year = 2012 Budget (in millions) = 911Year = 2013 Budget (in millions) = 1483Year = 2014 Budget (in millions) = 1897 Predict the budget for 2020
Your younger brother, a fourth form practical geography student wishes to test whether there could be some relationship between annual visits to a local market by all residents surrounding that market. After a well-designed field study he obtains the following figures: Number of visits per year 21 13 19 18 17 17 14 20 10 11 Residence distance from market (KM) 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 From the information above, what is the dependent variable and what is the explanatory variable? Using (i) above, obtain the regression equation of Yi on Xi. Hence, estimate the residence distance from the market (in KM) if the number of visits are 16 visits Sketch your results in (ii) above. What conclusion can you draw from your sketch?
This dataset of size n - 51 is for the 50 states and the District of Columbia in the United States. The variables are - year 2002 birth rate per 1000 females 15 to 17 years old and z- poverty rate (the percent of the state's population living in households with in- comes below the federally defined poverty level) i- 13.1 - 22.3 R- 51, Su - E(-2) - 914.7 S, - E( -2)( - 6) - 1, 256.2 Su - E(m - M) - 3, 249 SSE - E(w - - 1, 509.6 1. Find A. A and r. 2. Write the fitted linear regression model for ý, in terms of z, A, and A- For A and , use the values you obtained in problem 1. 3. Interpret the slope of the least squares line based on the context. 4. Find SST, SE and SSR. 5. Find R* and . 6. Complete a chart for ANOVA df MS pvalue Source Regression Error Total 7. Complete a chart for Parameter Estimates. t-value pvalue Parameter Intercept Slope Estimate S.e. 8. What is the residual e, for the observation (.) - (20.1,31.5)? 9. What is the conclusion for the test Ha : -0 vs Ho : +0 with a -…
Which model—the one for parliaments or the one for ministries (or cabinets)—presented in the article has the greater explanatory power? How can you tell?
The following data show Transportation Budget for North Carolina (Let year 1- 2003)Year = 2003 Budget (in millions) = 385Year = 2004 Budget (in millions) = 397Year = 2005 Budget (in millions) = 452Year = 2006 Budget (in millions) = 501Year = 2007 Budget (in millions) = 446Year = 2008 Budget (in millions) = 450Year = 2009 Budget (in millions) = 593Year = 2010 Budget (in millions) = 654Year = 2011 Budget (in millions) = 846Year = 2012 Budget (in millions) = 911Year = 2013 Budget (in millions) = 1483Year = 2014 Budget (in millions) = 1897a) Create a scatter plot and be sure to LABEL BOTH axis and give the chart an overall name. Have the graph display the “r-value” and the correct equation.b) What kind of correlation is this?c) Is this more of a linear or exponential model? Why?d) Predict the budget for 2020
My data sets were given in one of two pictures which I sent
In this data what is the independent variable and what is the dependent variable?
The table lists the average gestation period (in days) and longevity (in years) for the following mammals, as reported in The World Almanac and Book of Facts 2006. Mammal Gestation, y(days) Longevity, x(years) Mammal Gestation, y(days) Longevity, x(years) Baboon 187 20 Camel 406 12 Bear, black 219 18 Cat 63 12 Bear, grizzly 225 25 Chimpanzee 230 20 Bear, polar 240 20 Chipmunk 31 6 Beaver 105 5 Cow 284 15 Buffalo 285 15 Deer 201 8 Dog 61 12 Monkey 164 15 Donkey 365 12 Moose 240 12 Elephant 645 40 Mouse 21 3 Elk 250 15 Opossum 13 1 Fox 52 7 Pig 112 10 Giraffe 457 10 Puma 90 12 Goat 151 8 Rabbit 31 5 Gorilla 258 20 Rhinoceros 450 15 Guinea pig 48 4 Sea lion 350 12 Hippopotamus 238 41 Sheep 154 12 Horse 330 20 Squirrel 44 10 Kangaroo…
The following table lists highway miles (in MPG) and weight (in pounds) for a variety of cars, foreign and domestic (same data as before). CAR HWY WEIGHT Chev. Cavalier 31 2795 Lincoln Cont. 24 3930 Mitsubishi Eclipse 33 3235 Olds. Aurora 26 3995 Pontiac Grand Am 30 3115 Chev. Corvette 28 3220 BMW 3-Series 27 3225 Ford Crown Victoria 24 3985 Hyundai Accent If we let x be the weight and y be the Highway MPG, and we used Excel to compute the equation of the Least- 37 2290 Square regression line (which comes out to be y = -0.00672'x + 51.1156) as well as the correlation coefficient (which comes out to be -0.89). Then you used that equation to predict that the Highway Miles for a car that weighs just 1000 pounds would be 44.4 mpg. I think this prediction is accurate because the person used Excel for the computation. O I think this prediction is not accurate since a car that weighs 1000 pounds is not part of the original data list. O Ithink this prediction is not accurate because the person…
The table lists the average gestation period (in days) and longevity (in years) for the following mammals, as reported in The World Almanac and Book of Facts 2006. Mammal Gestation, y(days) Longevity, x(years) Mammal Gestation, y(days) Longevity, x(years) Baboon 187 20 Camel 406 12 Bear, black 219 18 Cat 63 12 Bear, grizzly 225 25 Chimpanzee 230 20 Bear, polar 240 20 Chipmunk 31 6 Beaver 105 5 Cow 284 15 Buffalo 285 15 Deer 201 8 Dog 61 12 Monkey 164 15 Donkey 365 12 Moose 240 12 Elephant 645 40 Mouse 21 3 Elk 250 15 Opossum 13 1 Fox 52 7 Pig 112 10 Giraffe 457 10 Puma 90 12 Goat 151 8 Rabbit 31 5 Gorilla 258 20 Rhinoceros 450 15 Guinea pig 48 4 Sea lion 350 12 Hippopotamus 238 41 Sheep 154 12 Horse 330 20 Squirrel 44 10 Kangaroo…
2. Two different statistics. Statistic A and Statistic B. are used to estimate the same population parameter. Statistic A has less variability than Statistic B and Statistic A has less bias than Statistic B. Using the axes below, draw parallel dotplots showing 10 values of each statistic that are consistent with these characteristics. Assume that the parameter value is at the arrow on the axes. Statistic A Statistic B
. Primary Data Source and Secondary Data Source ?