Quantitative Methods

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In a multiple regression analysis involving 10 independent variables and 81 observations, SST = 120 and SSE = 42. The multiple coefficient of determination is

.65.

In regression analysis, the error term ε is a random variable with a mean or expected value of

0

A regression model involved 5 independent variables and 136 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have

130 degrees of freedom.

In an analysis of variance problem involving 3 treatments and 10 observations per treatment, SSE = 399.6. The MSE for this situation is

14.8

In an analysis of variance problem involving 3 treatments and 10 observations per treatment, SSE = 399.6. The MSE for this situation is

14.8.

A regression model involved 18 independent variables and 200 observations. The critical value of t for testing the significance of each of the independent variable's coefficients will have

181 degrees of freedom.

In a multiple regression model involving 44 observations, the following estimated regression equation was obtained. ​ y ^ = 29 + 18x1 + 43x2 + 87x3 ​ For this model, SSR = 600 and SSE = 400. MSR for this model is

200.

In order to test for the significance of a regression model involving 3 independent variables and 47 observations, the numerator and denominator degrees of freedom (respectively) for the critical value of F are

3 and 43.

An ANOVA procedure is used for data obtained from four populations. Four samples, each comprised of 25 observations, were taken from the four populations. The numerator and denominator (respectively) degrees of freedom for the critical value of F are

3 and 96.

An ANOVA procedure is used for data that was obtained from five sample groups each comprised of six observations. The degrees of freedom for the critical value of F are

4 and 25.

In an analysis of variance problem if SST = 120 and SSTR = 80, then SSE is

40

An ANOVA procedure is applied to data obtained from 6 samples where each sample contains 20 observations. The critical value of F occurs with

5 numerator and 114 denominator degrees of freedom

We use non-parametric ANOVA instead of parametric ANOVA if

All of the above

In a regression model involving more than one independent variable, which of the following tests must be used in order to determine if the relationship between the dependent variable and the set of independent variables is significant?

F test

The F ratio in a completely randomized ANOVA is given by

MSTR/MSE.

Non-parametric ANOVA test on:

Median

What is the assumption not required for non-parametric ANOVA?

Population are not normally distributed

Which of the following is not a required assumption for the analysis of variance?

Populations under consideration have equal means.

In an analysis of variance where the total sample size for the experiment is and the number of populations is k, the mean square due to error is

SSE/(n T - k).

In an analysis of variance where the total sample size for the experiment is nT and the number of populations is k, the mean square due to error is

SSE/(n T - k).

The correct relationship between SST, SSR, and SSE is given by

SSR = SST - SSE.

Which of the following is correct?

SST = SSR + SSE

When an analysis of variance is performed on samples drawn from k populations, the mean square due to treatments (MSTR) is

SSTR/(k - 1).

In regression analysis, which of the following assumptions is not true about the error term ε?

The expected value of the error term is one.

A variable that takes on the values of 0 or 1 and is used to incorporate the effect of categorical independent variables in a regression model is called

a dummy variable.

The mathematical equation which has the form of E(y) = β0 + β1x 1+ β2x 2+ ... + βpx prelating the expected value of the dependent variable to the value of the independent variables is

a multiple regression equation.

The equation which has the form of E(y) = y ^= b0 + b1 x 1+ b2 x 2+ ... + bp x pis

an estimated multiple regression equation.

The process of using the same or similar experimental units for all treatments is called

blocking.

The coefficient of determination

cannot be negative.

The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the​

coefficient of determination.

An experimental design where the experimental units are randomly assigned to the treatments is known as _____ design.

completely randomized design.

In regression analysis, the response variable is the

dependent variable.

In regression analysis, the variable that is being predicted is the

dependent variable.

In the ANOVA, treatments refer to

different levels of a factor.

In an ANOVA procedure, a term that means the same as the term "variable" is

factor

An experimental design that permits simultaneous statistical conclusions about two or more factors is a

factorial design.

A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function: ​ y ^= 7 - 3x1 + 5x2​ ​ For this model, SSR = 3500, SSE = 1500, and the sample size is 18. The coefficient of x2 indicates that if television advertisement is increased by $1 (holding the unit price constant), sales are expected to

increase by $5000.

A multiple regression model has the estimated form ​ y ^= 7 + 2x1 + 9x2 ​ As x1 increases by 1 unit (holding x2 constant), y is expected to

increase by 2 units.

A multiple regression model has the estimated form ​ y ^= 5 + 6x + 7w ​ As x increases by 1 unit (holding w constant), y is expected to

increase by 6 units.

A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function: ​ y ^= 7 - 3x1 + 5x2 ​ For this model, SSR = 3500, SSE = 1500, and the sample size is 18. The coefficient of the unit price indicates that if the unit price is

increased by $1 (holding advertisement constant), sales are expected to decrease by $3000.

In factorial designs, the response produced when the treatments of one factor interact with the treatments of another in influencing the response variable is known as

interaction.

The mean square is the sum of squares divided by

its corresponding degrees of freedom.

In testing for the equality of k population means, the number of treatments is​

k

If a categorical variable has k levels, the number of dummy variables required is

k - 1.

Larger values of R 2 imply that the observations are more closely grouped about the

least squares line.

A term used to describe the case when the independent variables in a multiple regression model are correlated is

multicollinearity.

The adjusted multiple coefficient of determination is adjusted for the

number of independent variables.

Regression analysis is a statistical procedure for developing a mathematical equation that describes how

one dependent and one or more independent variables are related.

In an analysis of variance, one estimate of σ2 is based upon the differences between the treatment means and the

overall sample mean.

The required condition for using an ANOVA procedure on data from several populations is that the

sampled populations have equal variances.

If we are testing for the equality of three population means, we should use the​

test statistic F.

The ratio of MSR to MSE yields

the F statistic.

In the analysis of variance procedure (ANOVA), "factor" refers to

the independent variable.

In a regression model, the variance of the error term ε is assumed to be

the same for all values of the independent variable.

The ANOVA procedure is a statistical approach for determining whether or not the means of

three or more populations are equal.

In regression analysis, the independent variable is

used to predict the dependent variable.

In ANOVA, which of the following is not affected by whether or not the population means are equal?

within-treatments estimate of σ 2

In a factorial experiment, if there are x levels of factor A and y levels of factor B, there is a total of​

xy treatment combinations.

In a regression model, the error term ε is assumed to be a random variable with a mean of

zero.


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