Choose: The logistic regression model shares the following assumption with the “regular” OLS regression model. 1)linear...
Choose: The logistic regression model shares the following assumption with the “regular” OLS regression model.
1)linear associations 2)normal distribution 3)homoscedasticity 4)homogeneity of variance
Homework Answers
Logistic regression does not require a linear relationship between the dependent and independent variables.
The error terms (residuals) do not need to be normally distributed.
Homoscedasticity is not required.
While homogenity of variance is to be followed by both.All the four are to be followed by linear regerssion too.
Add Answer to:
Choose: The logistic regression model shares the following
assumption with the “regular” OLS regression model.
1)linear...
Decide (with short explanations) whether the following statements are true or false. r) The error term in logistic regression has a binomial distribution s) The standard linear regression model (unde...
Decide (with short explanations) whether the following
statements are true or false.
r) The error term in logistic regression has a binomial distribution s) The standard linear regression model (under the assumption of normality) is not appropriate for modeling binomial response data t Backward and forward stepwise regression will generally provide different sets of selected variables when p, the number of predicting variables, is large. u) BIC penalizes for complexity of the model more than AIC
r) The error term...
Question 1: Which of the following would generally cause the variance of the OLS estimator of...
Question 1: Which of the following would generally cause the variance of the OLS estimator of the slope in a regression model to be larger? 1) smaller variance of the error term 2) a larger sample size 3) smaller variance of the independent variable 4) larger variance of Xi ------------------------------------------------------------------------------------------------------------------------------ Question 2: Which of the following is the best description of the sampling distribution of the OLS estimator under the least squares assumptions? 1) it is a Student's t distribution...
1. Choose all the valid answers to the description about linear regression and logistic regressio...
machine learning/ stats questions
1. Choose all the valid answers to the description about linear regression and logistic regression from the options below: A. Linear regression is an unsupervised learning problem; logistic regression is a super- vised learning problem. B. Linear regression deals with the prediction of co ontinuous values; logistic regression deals with the prediction of class labe C. We cannot use gradient descent to solve linear regression: we must resort to least square estimation to compute a closed-form...
Consider the following simple regression model: a. Suppose that OLS assumptions 1 to 4 hold true. We know that homoskedasticity assumption is statedas: Var[UjIx] = σ2 for all i Now, suppose that...
Consider the following simple regression model: a. Suppose that OLS assumptions 1 to 4 hold true. We know that homoskedasticity assumption is statedas: Var[UjIx] = σ2 for all i Now, suppose that homoskedasticity does not hold. Mathematically, this is expressed as In other words, the subscript i in σ12 means that the conditional variance of errors for each individual i is different. Under heteroskedasticity, we can derive the expression for the variance of Var(B) as SST Where SSTx is the...
Help with some data science questions Q.1 The linear regression model assumes multivariate normality, no or...
Help with some data science questions Q.1 The linear regression model assumes multivariate normality, no or little multicollinearity, no auto-correlation, and homoscedasticity? Which assumption is missing from this list? (no more than 10 words) Q.2 The coefficient of correlation measures the percent change in the feature variables explained by the target variables. a) True b) False Q.3 In a linear regression model, the coefficient measures the change in Y explained by one unit-change in X. a) True b) False Q4....
c) Which theorem gives th (a) State the OLS assumptions in a simple linear regression model....
c) Which theorem gives th (a) State the OLS assumptions in a simple linear regression model. (3) b] How do you modify the OLS assumptions if you have a control variable? (2) (c) Discuss the problem of omitted variable bias. (5)
1.Given the Multiple Linear regression model as Y-Po + β.X1 + β2X2 + β3Xs + which in matrix notation is written asy-xß +ε where -έ has a N(0,a21) distribution + + ßpXo +ε A. Show that the OLS estimat...
1.Given the Multiple Linear regression model as Y-Po + β.X1 + β2X2 + β3Xs + which in matrix notation is written asy-xß +ε where -έ has a N(0,a21) distribution + + ßpXo +ε A. Show that the OLS estimator of the parameter vector B is given by B. Show that the OLS in A above is an unbiased estimator of β Hint: E(β)-β C. Show that the variance of the estimator is Var(B)-o(Xx)-1 D. What is the distribution o the...
Prove that the OLS estimator As for β in the linear regression model is consistent Let's first sh...
Taking the yellow parts below as a model to solve the
question above. Thank you!!!!!!!!
Prove that the OLS estimator As for β in the linear regression model is consistent Let's first show that the OLS estimator is consistent Recall the result for β LS-(Lil Xix;厂E-1 xīYi Using Yi = X(B* + ui By the WLLN Assuming that E(X,X is non-negative definite (so that its inverse exists) and using Slutsky's theorem It follows In words: ßOLs converges in probability to...
Answer each question by writing TRUE or FALSE 1. For OLS estimators to be linear the...
Answer each question by writing TRUE or FALSE 1. For OLS estimators to be linear the explanatory variables must be variable, non- stochastic and fixed in repeated samples. Under the conditions of perfect multicollinearity, the OLS estimators are not unique. The presence of heteroskedasticity causes the OLS method to overestimate the variances 2. 3. of the parameters. The Breusch-Godfrey LM test is applicable when a lagged dependent variable is used. If we include a non-influential variable in an equation the...
6. This problem considers the simple linear regression model, that is, a model with a single...
6. This problem considers the simple linear regression model, that is, a model with a single covariate r that has a linear relationship with a response y. This simple linear regression model is y = Bo + Bix +, where Bo and Bi are unknown constants, and a random error has normal distribution with mean 0 and unknown variance o' The covariate a is often controlled by data analyst and measured with negligible error, while y is a random variable....
Decide (with short explanations) whether the following
statements are true or false.
r) The error term in logistic regression has a binomial distribution s) The standard linear regression model (under the assumption of normality) is not appropriate for modeling binomial response data t Backward and forward stepwise regression will generally provide different sets of selected variables when p, the number of predicting variables, is large. u) BIC penalizes for complexity of the model more than AIC
r) The error term...
machine learning/ stats questions
1. Choose all the valid answers to the description about linear regression and logistic regression from the options below: A. Linear regression is an unsupervised learning problem; logistic regression is a super- vised learning problem. B. Linear regression deals with the prediction of co ontinuous values; logistic regression deals with the prediction of class labe C. We cannot use gradient descent to solve linear regression: we must resort to least square estimation to compute a closed-form...
Consider the following simple regression model: a. Suppose that OLS assumptions 1 to 4 hold true. We know that homoskedasticity assumption is statedas: Var[UjIx] = σ2 for all i Now, suppose that homoskedasticity does not hold. Mathematically, this is expressed as In other words, the subscript i in σ12 means that the conditional variance of errors for each individual i is different. Under heteroskedasticity, we can derive the expression for the variance of Var(B) as SST Where SSTx is the...
c) Which theorem gives th (a) State the OLS assumptions in a simple linear regression model. (3) b] How do you modify the OLS assumptions if you have a control variable? (2) (c) Discuss the problem of omitted variable bias. (5)
1.Given the Multiple Linear regression model as Y-Po + β.X1 + β2X2 + β3Xs + which in matrix notation is written asy-xß +ε where -έ has a N(0,a21) distribution + + ßpXo +ε A. Show that the OLS estimator of the parameter vector B is given by B. Show that the OLS in A above is an unbiased estimator of β Hint: E(β)-β C. Show that the variance of the estimator is Var(B)-o(Xx)-1 D. What is the distribution o the...
Taking the yellow parts below as a model to solve the
question above. Thank you!!!!!!!!
Prove that the OLS estimator As for β in the linear regression model is consistent Let's first show that the OLS estimator is consistent Recall the result for β LS-(Lil Xix;厂E-1 xīYi Using Yi = X(B* + ui By the WLLN Assuming that E(X,X is non-negative definite (so that its inverse exists) and using Slutsky's theorem It follows In words: ßOLs converges in probability to...
Answer each question by writing TRUE or FALSE 1. For OLS estimators to be linear the explanatory variables must be variable, non- stochastic and fixed in repeated samples. Under the conditions of perfect multicollinearity, the OLS estimators are not unique. The presence of heteroskedasticity causes the OLS method to overestimate the variances 2. 3. of the parameters. The Breusch-Godfrey LM test is applicable when a lagged dependent variable is used. If we include a non-influential variable in an equation the...
6. This problem considers the simple linear regression model, that is, a model with a single covariate r that has a linear relationship with a response y. This simple linear regression model is y = Bo + Bix +, where Bo and Bi are unknown constants, and a random error has normal distribution with mean 0 and unknown variance o' The covariate a is often controlled by data analyst and measured with negligible error, while y is a random variable....
Most questions answered within 3 hours.
-
which of the following may lead to speciation?
a. a group of individuals from a mainland...
asked 4 minutes ago -
Please I need today answer for This question and it is very
important and I need...
asked 23 minutes ago -
Five years from today, you plan to invest $3,700 for 7
additional years at 5.8 percent...
asked 23 minutes ago -
GDL just paid a dividend of $4.06 per share. You expect
dividends to grow 12% for...
asked 24 minutes ago -
which of the following is a basic compound?
vinegar
orange juice
seltzer
none of the above
asked 27 minutes ago -
5. Suppose you obtained 0.55 g of crude clove oil from 7.0 g of
fresh cloves....
asked 37 minutes ago -
Provide a paragraph of introduction that generally describes
cognitive development over the lifespan.
asked 42 minutes ago -
In a market, when the price increased the total expenditure on
the good also increased. Is...
asked 42 minutes ago -
If 5.70 g of potassium react with water, how many grams of
hydrogen gas, H2, are...
asked 56 minutes ago -
How many moles of CO2 and H2O will be
produced by combustion analysis of 0.010 mol...
asked 54 minutes ago -
Tennis champion Maria Sharapova is capable of serving a tennis
ball at 126 mph.
b) What...
asked 1 hour ago -
The electric potential V in the space between the plates of a
given vacuum tube is...
asked 1 hour ago