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    the parameters of nonlinear models have exponents _____.

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    The parameters of nonlinear models have exponents _____. a. larger than 0 b. other than 1 c.

    Click here 👆 to get an answer to your question ✍️ The parameters of nonlinear models have exponents _____. a. larger than 0 b. other than 1 c. larger than 3…

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    The parameters of nonlinear models have exponents _____.

    a. larger than 0 b. other than 1 c. larger than 3 d. only equal to 2

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    Answer:

    b. other than 1

    Explanation:

    Nonlinear models are called that way because they are not linear in parameters. In order for this nonlinear characteristic to exist, the exponents of the parameters must be any number other than 1.

    While linear models can have a nonlinear relationship between the predictors and independent variables. But when you analyze the mean (predictor), it must be linear with the parameters.

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    Expert-verified answer

    The nonlinear models have an exponent other than 1. As the nonlinear exponent estimating a regression model, convert the forecast variable y and/or the predictor variable x.

    What is the nonlinear model?

    Non-linearity is a term used in statistics to describe a situation where there is no direct relationship between the two variables that are independent and independent. The input is not directly affected by the change in the relationship in the output in the direct proposition.

    Thus, option B is correct.

    For further details about the non-linear model refer to this link:

    https://brainly.in/question/1327517

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    qmb test 3 Flashcards

    Study with Quizlet and memorize flashcards terms like What test can be used to determine whether first-order autocorrelation is present, When determining the best estimated regression equation to model a set of data, the procedure that allows an independent variable to enter the model at one step, be removed at a subsequent step, and then enter the model at a later step is, The variable selection procedure that identifies the best regression equation, given a specified number of independent variables, is: and more.

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    14 studiers in the last day

    What test can be used to determine whether first-order autocorrelation is present

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    Durbin-Watson test

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    When determining the best estimated regression equation to model a set of data, the procedure that allows an independent variable to enter the model at one step, be removed at a subsequent step, and then enter the model at a later step is

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    stepwise regression

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    1/29 Created by noahbrandes1

    Terms in this set (29)

    What test can be used to determine whether first-order autocorrelation is present

    Durbin-Watson test

    When determining the best estimated regression equation to model a set of data, the procedure that allows an independent variable to enter the model at one step, be removed at a subsequent step, and then enter the model at a later step is

    stepwise regression

    The variable selection procedure that identifies the best regression equation, given a specified number of independent variables, is:

    best-subsets regression

    When autocorrelation is present, which of the following assumptions is violated

    the error terms are independent

    The parameters of nonlinear models have exponents

    other than one

    The regression model is a

    second order model with one predictor value

    In multiple regression analysis, the general linear model:

    can be used to accommodate curvilinear relationships between the independent variables and the dependent variable

    The effect of two independent variables acting together is called:

    interaction

    In order to use the output from a multiple regression model to perform the ANOVA test on the difference among the means of four populations, how many dummy variables do we need to use to indicate treatments

    3: (K-1): (4-1)=3

    The Durbin-Watson test is generally inconclusive for:

    smaller sample sizes

    Which of the following options guarantees that the best model for a given number of variables will be found

    Best-subsets regression

    With negative autocorrelation, we expect a positive residual in one period to be followed by:

    a negative residual in the next period, then a positive residual, and so on

    When dealing with the problem of nonconstant variance, we can apply the reciprocal transformation, which means that we use:

    1/Y as the dependent variable instead of Y

    A model in the form of , where each independent variable zj (for j = 1, 2,..., p) is a function of x1, x2,..., xk, is known as the:

    ?????

    When carrying out an F test to determine if the addition of extra predictor variables results in a significant reduction in the error sum of squares, what are the degrees of freedom of the numerator and denominator of the F statistic?

    The numerator degrees of freedom equals the number of predictors added to the model. The denominator degrees of freedom is n—p—1.

    Which of the following statements about the backward elimination procedure is false?

    A:It is an iterative procedure.

    B:It does not guarantee that the best regression model will be found.

    C:***It begins with zero independent variables.

    D:It does not permit an independent variable to be reentered once it has been removed

    How many independent variables does the forward selection process start with

    Zero

    What value of Durbin-Watson statistic indicates that no autocorrelation is present

    Two

    the regression model

    second-order model with two predictor variables.

    Write a multiple regression equation that can be used to analyze the data for a two-factorial design with two levels for factor A and four levels for factor B.

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    Suppose a high correlation existed between variables x 1 and x 2 . If variable x 1 was used as an independent variable, then variable x

    would not add much more explanatory power to the current mode

    Correlation in the errors that arises when the error terms at successive points in time are related is called

    Autocorrelation

    Which of the following is not an iterative variable selection procedure

    A:Backward elimination

    B:Stepwise regression

    C:***Best-subsets regression

    D:Forward selection

    Looking at the sample correlation coefficients between the response variable and each of the independent variables can give us a quick indication of which independent variables are, by themselves

    Good predictors

    The range of the Durbin-Watson statistic is

    0-4

    When determining the best estimated regression equation to model a set of data, the procedure that begins each step by determining whether any of the variables already in the model should be removed is called

    stepwise regression

    If the value of y in time period t is related to its value in time period t - 1, we say that

    first-order auto correlation is present

    Multicollinearity can cause problems if the absolute value of the sample correlation coefficient exceeds

    .7 for any two of the independent variables.

    In best-subsets regression, Minitab can be used to provide output that identifies the two best one-variable estimated regression equations, the two best two-variable estimated regression equations, the two best three-variable estimated regression equations, and so on. What criterion is used in determining which estimated regression equations are best

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