1- Assume one of the an explanatory a variable (named X1) in your logistic regression is...
1- Assume one of the an explanatory a variable (named X1) in your logistic regression is a categorical variable with the following levels: low, average and high, and another explanatory variable (named X2) is also categorical with the following levels: Sydney and Melbourne. Explain how you will use them in developing your logistic regression model. How many coefficients you will have in your final model?
2.Give two examples related to your discipline that you need to apply over sampling partitioning before building the model. You need to provide detail explanations
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1- Assume one of the an explanatory a variable (named X1) in
your logistic regression is...
Assume a model with 1 numerical explanatory variable (x1) and 1 categorical explanatory variable with 2...
Assume a model with 1 numerical explanatory variable (x1) and 1
categorical explanatory variable with 2 category levels (Red,
Blue). Further assume the model includes the possibility that the
relationship between the numerical explanatory variable and the
response depends on the levels of the categorical variable (include
an interaction between the numerical and categorical variable).
x2 is defined to
take the value of 1 for Red and 0 for Blue.
The population model is
μy=β0+β1x1+β2x2+β3x1x2
The simplified version of the...
Decide (with short explanations) whether the following statements are true or false. e) In a simple linear regression model with explanatory variable x and outcome variable y, we have these summary s...
Decide (with short explanations) whether the following
statements are true or false.
e) In a simple linear regression model with explanatory variable x and outcome variable y, we have these summary statisties z-10, s/-3 sy-5 and у-20. For a new data point with x = 13, it is possible that the predicted value is y = 26. f A standard multiple regression model with continuous predictors and r2, a categorical predictor T with four values, an interaction between a and...
Use the following linear regression equation to answer the questions. x1 = 1.5 + 3.4x2 – 8.3x3 + 2.3x4 (a) Which variable is the response variable? Which variables are the explanatory variables? (b...
Use the following linear regression equation to answer the questions. x1 = 1.5 + 3.4x2 – 8.3x3 + 2.3x4 (a) Which variable is the response variable? Which variables are the explanatory variables? (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant? x2 coefficient? x3 coefficient? x4 coefficient? (c) If x2 = 1, x3 = 8, and x4 = 6, what is the predicted value for x1? (Use 1 decimal place.) (d) Explain how...
1. Consider the following linear regression model: (a) Which assumptions are needed to make the B,...
1. Consider the following linear regression model: (a) Which assumptions are needed to make the B, unbiased estimators for the B, (b) Explain how one can test the hypothesis that A +As = 0 by means of a t-test. (c) Explain how one can test the hypothesis that A-A-0. Indicate the relevant test statistic. (d) Suppose that ri is an irrelevant explanatory variable in the population model and that you estimate the model including both and r2. What are the...
Use the following linear regression equation to answer the questions. X1 = 1.7 + 3.6x2 -...
Use the following linear regression equation to answer the questions. X1 = 1.7 + 3.6x2 - 8.4x3 + 1.5x4 (a) Which variable is the response variable? O X1 O X2 O X4 O X3 Which variables are the explanatory variables? (Select all that apply.) X3 X1 U X2 (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient X3 coefficient X4 coefficient (c) If x2 = 8, X3 = 5, and x4...
a) Find the multiple regression equation using all three explanatory variables. Assume that X1 is mid-term...
a) Find the multiple regression equation using all three explanatory variables. Assume that X1 is mid-term score, X2 is hours studying per week and x3 is hours watching television per week. Give your answers to 3 decimal places. û = mid-term score + hours studying + hours watching television + b) At a level of significance of 0.05, the result of the F test for this model is that the null hypothesis rejected. c) The explanatory variable that is most...
Where appropriate, linear regression with one explanatory variable can be performed through the o...
Where appropriate, linear regression with one explanatory variable can be performed through the origin', that is, with the intercept α fixed equal to zero. The log-likelihood in this reduced model is So(B) 1(8, o)-constant-n log ơ--2 where 7 (by setting α = 0 in Equations (11.5) and (11.6) in subsection 2.1 of Unit 11). Solve the equation dS。(β)/dd = 0 to provide the candidate value fy for the value of β that minimises So(1) (it can be confirmed that β...
Use the following linear regression equation to answer the questions. x1 = 1.7 + 3.9x2 -...
Use the following linear regression equation to answer the questions. x1 = 1.7 + 3.9x2 - 8.1X3 + 1.9x4 (a) Which variable is the response variable? O O O O Which variables are the explanatory variables? (Select all that apply.) o X3 O X4 Сх, (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient Xz coefficient x4 coefficient (C) If x2 = 8, X3 = 3, and X4 = 1, what...
3. A researcher collected data to study the effect of smoking on the risk of a heart attack. The variables were x - a categorical variable with the categories: (1) Present smoker (2) Past smoker (...
3. A researcher collected data to study the effect of smoking on the risk of a heart attack. The variables were x - a categorical variable with the categories: (1) Present smoker (2) Past smoker (smoked but quit) (3) Non-smoker Y - a binary variable defined by: Y 1 if the person had a heart attack Y-0 if the person didn't have a heart attack Since the X-variables are categorical, the researcher coded the X-variable by two dummy variables: X2...
HELP ASAP Suppose you are wishing to fit a multiple linear regression model using one categorical...
HELP ASAP
Suppose you are wishing to fit a multiple linear regression model using one categorical variable that can take on 17 different values. For example, if you wished to use the months of the year in your model, the categorical variable "month" would have 12 different values: January, February, March, etc. In general, how many dummy variables would you need to incorporate into your model to completely capture the effect of all 17 conditions of a categorical variable on...
Assume a model with 1 numerical explanatory variable (x1) and 1
categorical explanatory variable with 2 category levels (Red,
Blue). Further assume the model includes the possibility that the
relationship between the numerical explanatory variable and the
response depends on the levels of the categorical variable (include
an interaction between the numerical and categorical variable).
x2 is defined to
take the value of 1 for Red and 0 for Blue.
The population model is
μy=β0+β1x1+β2x2+β3x1x2
The simplified version of the...
Decide (with short explanations) whether the following
statements are true or false.
e) In a simple linear regression model with explanatory variable x and outcome variable y, we have these summary statisties z-10, s/-3 sy-5 and у-20. For a new data point with x = 13, it is possible that the predicted value is y = 26. f A standard multiple regression model with continuous predictors and r2, a categorical predictor T with four values, an interaction between a and...
1. Consider the following linear regression model: (a) Which assumptions are needed to make the B, unbiased estimators for the B, (b) Explain how one can test the hypothesis that A +As = 0 by means of a t-test. (c) Explain how one can test the hypothesis that A-A-0. Indicate the relevant test statistic. (d) Suppose that ri is an irrelevant explanatory variable in the population model and that you estimate the model including both and r2. What are the...
Use the following linear regression equation to answer the questions. X1 = 1.7 + 3.6x2 - 8.4x3 + 1.5x4 (a) Which variable is the response variable? O X1 O X2 O X4 O X3 Which variables are the explanatory variables? (Select all that apply.) X3 X1 U X2 (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient X3 coefficient X4 coefficient (c) If x2 = 8, X3 = 5, and x4...
a) Find the multiple regression equation using all three explanatory variables. Assume that X1 is mid-term score, X2 is hours studying per week and x3 is hours watching television per week. Give your answers to 3 decimal places. û = mid-term score + hours studying + hours watching television + b) At a level of significance of 0.05, the result of the F test for this model is that the null hypothesis rejected. c) The explanatory variable that is most...
Where appropriate, linear regression with one explanatory variable can be performed through the origin', that is, with the intercept α fixed equal to zero. The log-likelihood in this reduced model is So(B) 1(8, o)-constant-n log ơ--2 where 7 (by setting α = 0 in Equations (11.5) and (11.6) in subsection 2.1 of Unit 11). Solve the equation dS。(β)/dd = 0 to provide the candidate value fy for the value of β that minimises So(1) (it can be confirmed that β...
Use the following linear regression equation to answer the questions. x1 = 1.7 + 3.9x2 - 8.1X3 + 1.9x4 (a) Which variable is the response variable? O O O O Which variables are the explanatory variables? (Select all that apply.) o X3 O X4 Сх, (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant X2 coefficient Xz coefficient x4 coefficient (C) If x2 = 8, X3 = 3, and X4 = 1, what...
3. A researcher collected data to study the effect of smoking on the risk of a heart attack. The variables were x - a categorical variable with the categories: (1) Present smoker (2) Past smoker (smoked but quit) (3) Non-smoker Y - a binary variable defined by: Y 1 if the person had a heart attack Y-0 if the person didn't have a heart attack Since the X-variables are categorical, the researcher coded the X-variable by two dummy variables: X2...
HELP ASAP
Suppose you are wishing to fit a multiple linear regression model using one categorical variable that can take on 17 different values. For example, if you wished to use the months of the year in your model, the categorical variable "month" would have 12 different values: January, February, March, etc. In general, how many dummy variables would you need to incorporate into your model to completely capture the effect of all 17 conditions of a categorical variable on...
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