`Hey,
Note: If you have any queries related the answer please do comment. I would be very happy to resolve all your queries.
The logit is 1.529
SO, OPTION B IS CORRECT
Kindly revert for any queries
Thanks.
Consider a new data record whose Experience level is 9 and Training level is 4. From...
8. A regression of wage (log(wage) is run on a set of following variables: female (-1 if female), educ (years of education), exper (years of experience) and tenure (years with current employer). The regression results are listed as follows. Coefficients: Estimate Std. Error tvalue Pr(Itl) (Intercept) -1.56794 0.72455 -2.164 0.0309 female -1.81085 0.26483 -6.838 2.26e-11*** educ 0.57150 0.04934 11.584 <2e-16*** 0.02540 0.01157 2.195 0.0286 exper 0.14101 0.02116 6.663 6.83e-11*** tenure Signif. codes:0.0010.010.050.1'"1 Residual standard error: 2.958 on 521 degrees of...
8. A regression of wage (log(wage) is run on a set of following variables: female (-1 if female), educ (years of education), exper (years of experience) and tenure (years with current employer). The regression results are listed as follows. Coefficients: Estimate Std. Error tvalue Pr(Itl) (Intercept) -1.56794 0.72455 -2.164 0.0309 female -1.81085 0.26483 -6.838 2.26e-11*** educ 0.57150 0.04934 11.584 <2e-16*** 0.02540 0.01157 2.195 0.0286 exper 0.14101 0.02116 6.663 6.83e-11*** tenure Signif. codes:0.0010.010.050.1'"1 Residual standard error: 2.958 on 521 degrees of...
8. A regression of wage (log(wage) is run on a set of following variables: female (-1 if female), educ (years of education), exper (years of experience) and tenure (years with current employer). The regression results are listed as follows. Coefficients: Estimate Std. Error tvalue Pr(Itl) (Intercept) -1.56794 0.72455 -2.164 0.0309 female -1.81085 0.26483 -6.838 2.26e-11*** educ 0.57150 0.04934 11.584 <2e-16*** 0.02540 0.01157 2.195 0.0286 exper 0.14101 0.02116 6.663 6.83e-11*** tenure Signif. codes:0.0010.010.050.1'"1 Residual standard error: 2.958 on 521 degrees of...
Consider Model 1 from Individual Assignment 2. Use this regression model to test (at the 5% level of significance) if the average price of a house in the East neighborhood is less than the average price of a similar house in the North neighborhood. StatTools Report Analysis: Regression Performed By: Bardossy Date: Friday, September 27, 2019 Updating: Static Variable Price Multiple Multiple Regression for Price Summary R-Square Rows Ignored Outliers Adjusted R-square 0.8578 Std. Err. of Estimate 50660.95358 0.9304 0.8656...
You are working for the marketing team of a major bank. The bank has collected data from a recent sales campaign, where the outcome of interest, Y, is whether or not a customer signs up for a new type of account (1=Yes; 0=No). To try to understand the relationship between customer education level and the probability that he or she will sign up for the new account, your boss asks you to run a logistic regression model. The model is...
26) A study in transportation safety collected data on 42 North American cities. From each city, two of the variables recorded were X = percentage of licensed drivers who are under 21 years of age, and Y = the number of fatal accidents per year per 1000 licenses. Below is the output from the data: Parameter Intercept Std. Estimate -1.59741 Error 0.371671 T Statistic -4.29792 p-value 0.0001 0.0293898 9.76711 0.0000 Slope 0.287053 Correlation coefficient = 0.839387 R-squared = 70.4571 percent...
Credit card fraud is fraud perpetrated through stolen credit cards or credit card information. For years, credit card issuers have been using data mining and statistical tools to detect fraud. Citibank reported that knowing the type of product or service bought, frequency of purchases, and size and location of transaction can significantly reduce fraud. (Source: Jesus Mena, Investigative Data Mining for Security and Criminal Detection, Butterworth-Heinemann, pp. 250-251) A data-mining analyst at a major credit card company would like to...
Use the following for question 8 to 10. Silicon-germanium alloys have been used in certain types of solar cells. Researchers investigated how germanium (Ge) concentration affected the Fermi level position (eV). Assume all observations are independent. We have the following results. Simple linear regression results Dependent Variable : Fermi level Independent Variable : Ge Fermi level = 0.721786 - 0.43268475 Ge Sample size : 13 R (correlation coefficient) = -0.073757327 R-sq = 0.80156604 Estimate of error standard deviation = 0.073757327...
A regression analysis is performed using data for 36
single-family homes to predict appraised value (in thousands of
dollars) based on land area of the property (in acres), X1i, and
age (in years), X2i, in month i. Use the results below to
complete parts (a) and (b) below.
Variable
Coefficient
Standard Error
t Statistic
p-value
Intercept
392.60372
51.68272
7.60
0.0000
Area, X1
451.43475
100.48497
4.49
0.0001
Age,X2
−2.17162
0.79077
−2.75
0.0097
a. Construct a 95% confidence interval estimate...
I need help interpreting logistic regression results to answer
the following question: Does GRE scores, undergraduate GPA and the
prestige (yes or no) of their undergraduate program effect
admission (yes or no) into graduate school?
Fit Group 4 Logistic Fit of ADMIT 2 By GRE 1.00 Contingency Analysis of ADMIT 2 By TOPNOTCH 2 4 Mosaic Plot Logistic Fit of ADMIT 2 By GPA 1.00 1.00 0.75 0.75 No 0.75 No No ADMIT 2 0.50 N 0.50 ADMIT 2 ADMIT...