Suppose a logistic regression model is fitted for the probability of car ownership for residents of a certain city in Oman (Y=1 if aresident owns a car, Y=0 ifa resident does not own a car). Suppose the explanatory variables used are x1=no. of years a resident spent in schooling and x2 is gender of the resident of the city (x2=1 for a male and x2 0 for a female resident) a) Interpret el and e2 b) if BO= -1.6, B1-0.4 and B2 3, estimate the probability of a resident in the ituownin
Q: What is the expected weight of a chimpanzee that is 157 cm tall?
A: Here Given Regression Equation Y = 0.34x + 19.5 Where Y = Weight in Kg x = Height in cm And…
Q: Suppose Wesley is a marine biologist who is interested in the relationship between the age and the…
A:
Q: Suppose that a least squares regression line equation is ˆy = 1.65 − 2.20x and the actual y value…
A: Residual value:The difference between the calculated value and predicted value of a dependent…
Q: Suppose the following regression equation was generated from the sample data of 50 cities relating…
A: The objective of the question is to interpret the regression equation and determine which of the…
Q: A researcher interested in explaining the level of foreign reserves for the country of Barbados…
A: c) Given: Coeff of (EXP) B=-377.08 stdev = 112.19 The missing value of "*" The t-ratio for the…
Q: The administration of a midwestern university commissioned a salary equity study to help establish…
A: Introduction: In order to use a categorical variable into a model, dummy vectors are used, which…
Q: A researcher conducted a study about the hemoglobin levels among menopausal and non-menopausal…
A: The question is about logistic regression.Given :Coefficient estimate of intercept ( b0 ) =…
Q: A company advertises its product in different media. They have established a regression model to…
A: The regression method is the most usable concept for prediction. The multiple regression model can…
Q: If we collect monthly sales over two years for N=100 stores, we should not apply a simple linear…
A: If we collect monthly sales over two years for N=100 stores, we should not apply a simple linear…
Q: Suppose IQ scores were obtained from randomly selected twins. For 20 such pairs of people, the…
A:
Q: The table below gives the age and bone density for five randomly selected women. Using this data,…
A: The data values are as follow: x (age) y (bone density) 35 350 43 340 53 339 54 321 55…
Q: Suppose the following data were collected from a sample of 1515 CEOs relating annual salary to years…
A: The objective of this question is to determine whether there is enough evidence to support the claim…
Q: An observational study was conducted where subjects were randomly sampled and then had their resting…
A: Solution: Given information: n= 232 observation. k=3 independent variables. β2^= -7.3684 Slope…
Q: If o, = 0, - = o and the angle between the regression lines is tar . Find the coefficient of…
A:
Q: Which of the following statements about correlation r = 0.923 is TRUE? Circle ONE answer. No…
A: Given
Q: The pH levels and mercury levels of several lakes throughout Ohio are measured esearchers do a…
A: Regression analysis is a useful inferential method for forecasting.
Q: The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a…
A: Given, Dependent variable: Oil imported (y) Independent variable: Oil produced (x) n=7 df=(n-2) =…
Q: amount of time spent at the ATM machine (SECONDS) and the gender, FEMALE (dummy variable = 1 for…
A: It is given that seconds =27.
Q: 1. Fill in the blank: For these data, birthrates that are less than the mean of the birthrates tend…
A: 1. In the regression line we can see that the regression line has a negative slope that means if one…
Q: None
A: ### a. Estimating the Regression Model: To estimate the time until the first engine overhaul as a…
Q: The coefficient of correlation between the ages of husbands and wives in a community was found to be…
A: Solution is given below:
Q: The line of best fit through a set of data isy=38.397+4.038xy=38.397+4.038x According to this…
A: We have given that The line of best fit through a set of data is y=38.397+4.038x.
Q: In a study of possible correlation between the height in cm (X) and the weight in kg (Y) of…
A: Given that, Let the height be independent variable (X) and weight be dependent variable (Y). The…
Q: The least-squares regression equation is y=761.7x+13,208 where y is the median income and x is the…
A: The least-squares regression equation is y=761.7x+13208 The linear relation between the two…
Q: Suppose you are examining a multi-variable linear regression model that was designed to predict the…
A:
Q: 10) The following results are from a regression where the dependent variable is COST OF COLLEGE and…
A: Given the results of regression of dependent variable i.e the cost of the college and the…
Q: The line of best fit through a set of data is y = – 27.749 + 1.474x According to this equation, what…
A:
Q: estimated the following multiple regression model using yearly data spanning the period 2001 2016:…
A: The null and alternative hypotheses are The test statistic is given by t = 4626 p-value = 0.006…
Q: The maintenance manager at a trucking company wants to build a regression model to forecast the time…
A: Multiple linear regression model: A multiple linear regression model is given as y = b0 + b1x1 +…
Q: Compute the residual
A: here given regression line y = 24+5x residual = actual value - predicted value
Q: It is known that the slope coefficient for regression line Y on X is 0.942 The standard deviation of…
A: The slope of the regression line, bYX=0.942. The standard deviations of the variables, σX=5 and…
Q: One set of 20 pairs of scores, X and Y values, produces a correlation of r = 0.70. If SSY = 150,…
A: Given values, n=20r=0.70SSy=150
Q: The table below gives the age and bone density for five randomly selected women. Using this data,…
A: Age Bone Density35 35043 34053 33954 32155 310
Q: Suppose the entering freshmen at a certain college have a mean combined SAT score of 1231 with a…
A:
Q: & Puan Use wage1.txt data set for this question. Consider the following regression:…
A:
Q: Suppose a researcher collects data on houses that have been sold in a particular neighbourhood over…
A: Given the regression results of the houses data that have been sold in a particular neighborhood…
Q: It is known that the linear regression equation: y= -2.88+1.77x, with a coefficient of determination…
A:
Step by step
Solved in 2 steps
- 11. In this same article on sleep duration and start time, researchers also considered whether school start time was related to obtaining an adequate amount of sleep. An adequate amountbof sleep was considered at least 8.5 hours of sleep, as recommended by the National Sleep Foundation. The authors used logistic regression models to associate the probability of adequate sleep to school start time. Here are some adapted logistic regression results from this study: In(odds of adequate sleep) = 6, + B,, where x1 = school start time, measured as the number of minutes after 7 AM that the school starts. For this model, B,-0.014, SE(B,)-0.005. - What Is the estimated odds ratlo of adequate sleep, and 95% CI, for students who start at 8:30 AM compared to those who start at 7:30 AM? a. 1.01 (1.00, 1.02) b. 1.52 (1.13, 2.05) C. 2.32 (1.27, 4.22) d. 4.05 (1.49, 11.02)The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1^x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density35 35043 34053 33954 32155 310 Step 4 of 6 : Determine the value of the dependent variable yˆ at x=0.Suppose the following data were collected from a sample of 1515 CEOs relating annual salary to years of experience and the economic sector their company belongs to. Use statistical software to find the following regression equation: SALARYi=b0+b1EXPERIENCEi+b2SERVICEi+b3INDUSTRIALi+eiSALARY�=�0+�1EXPERIENCE�+�2SERVICE�+�3INDUSTRIAL�+��. Is there enough evidence to support the claim that on average, CEOs in the service sector have lower salaries than CEOs in the financial sector at the 0.010.01 level of significance? If yes, write the regression equation in the spaces provided with answers rounded to two decimal places. Else, select "There is not enough evidence." Copy Data CEO Salaries Salary Experience Service (1 if service sector, 0 otherwise) Industrial (1 if industrial sector, 0 otherwise) Financial (1 if financial sector, 0 otherwise) 144225144225 1010 11 00 00 187765187765 2020 00 00 11 142500142500 66 11 00 00 169650169650 2828 11 00 00 167250167250 3131 00…
- 2. I surveyed 150 adults in the U.S. and asked them how many hours of TV the watched on average per week. I then ran a regression of # of hours of TV on whether or not they were a college graduate (=1 if yes, =0 if no), their age in years, the number of children in their household, and whether or not they live a cold climate (=1 if latitude is greater than 41.2, =0 otherwise). The results fro the regression are shown in the table below. Estimate p-value College Graduate -0.8 0.003 Age 0.1 0.150 Number of Children 0.10 0.521 Cold Climate 1.8 0.047 Intercept -1.23 0.041 (a) What is the dependent variable in this regression? (b) What are the independent variable(s) in this regression? (c) What is the unit of analysis? (d) What is the sample size? (e) What is one binary variable used in this analysis? (f) What is one ratio variable used in this analysis? (g) What is the predicted number of TV hours watched by a 50 year old, colleg graduate, with no children at home who lives in Arizona…Can a causal relationship be established between a variable y and a variable x by running the following regressions: i) y = f(x) and ii) x = f(y). Explain in less than 75 words.This table reports the regression coefficients when the returns of the size-institutionalownership portfolio (columns 1 and 2) returns are regressed on three variables: a constant(column 3), the stock market returns (column 4), and the change of the value weighted discountof the closed end fund industry (column 6). Columns 5 and 7 report the corresponding t-statistics of the coefficient estimates. Note that a t-statistic with an absolute value above 1.96means the coefficient estimate is significantly different from 0 at the 1% level. Column 8reports the R square of the regressions. Column 9 reports the mean institutional ownership ofeach portfolio. The last column reports the F-statistics for a multivariate test of the null hypothesis that the coefficient on ΔVWD in the Low (L) ownership portfolio is equal to theHigh (H) ownership portfolio. Two-tailed p-values are in parentheses. 1. What is the main finding of this Table? 2. What is the explanation for…
- A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: FR=a+B0IL+YEXP+8FDI Where FR = yearly foreign reserves ($000°s), OIL = annual oil prices, EXP = yearly total exports ($000's) and FDI = annual foreign direct investment ($000`s). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 OIL 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 0.0057 FDI -396.99 160.66 -2.471 ** s = 2.45 R-sq = 96.3% R-sq (adj) = 95.3% Analysis of Variance Source DF MS F Regression 1991.31 663.77 ?? Error 12 77.4 6.45 Total 15 a) What is dependent and independent variables? b) Fully write out the regression equationSuppose the following regression equation was generated from the sample data of 50 cities relating number of cigarette packs sold per 1000 residents in one week to tax in dollars on one pack of cigarettes and if smoking is allowed in bars: PACKS, 58803.462982-1005.438507TAX, +284.030008BARS, + BARS, 1 if city / allows smoking in bars and BARS,= 0 if city i does not allow smoking in bars. This equation has an R² value of 0.305162, and the coefficient of BARS, has a value of 0,088136. Which of the following conclusions is valid? Answer Keypad Keyboard Shortcuts m Tables O If there is no cigarette tax in a city that allows smoking in bars, the approximate number of cigarette packs sold per 1000 people is 58803. O According to the regression equation, cities that allow smoking in bars have lower cigarette sales than cities that do not allow smoking in bars. O More than half of the variation in cigarette sales is explained by cigarette taxes and whether or not a city allows smoking in bars.…Suppose Wesley is a marine biologist who is interested in the relationship between the age and the size of male Dungeness crabs. Wesley collects data on 1,000 crabs and uses the data to develop the following least-squares regression line where ?X is the age of the crab in months and ?ˆY^ is the predicted value of ?Y, the size of the male crab in cm. ?ˆ=9.5603+0.3976?Y^=9.5603+0.3976X What is the value of ?ˆY^ when a male crab is 24.9118 months old? Provide your answer with precision to two decimal places. Y=
- 38. Which is the linear regression equation for a scatterplot with these points rounded to the nearest tenth: (4, 35), (6.5, 92), (2. 10). (5, 50), (6, 85), (10, 110)?Below are bivariate data O each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is ing birthrate and life expectancy information for y = 81.87 – 0.46x. Birthrate, x (number of births per 1000 pop.) Female life expectancy, y (in years) 85- 35.7 67.7 80- 41.5 63.9 75 31.9 63.3 19.9 73.0 70 50.5 60.4 65. 24.4 72.7 60- 50.1 63.2 55 13.8 72.5 50 50.3 54.6 45.6 57.9 15.9 76.2 Figure 1 26.6 71.9 Send data to Excel