Bustiness Stats 10,13,14,15

In regression analysis, an outlier is an observation whose a. mean is zero b. mean is larger than the standard deviation d. standard residual value is larger than +2 or less than -2. d. residual is zero

d. standard residual value is larger than +2 or less than -2

Which of the following is correct? a. SSE=SSR+SST B. SSR=SSE+SST C. SST=SSR+SSE D. SST=(SSR)^2

C. SST=SSR+SSE

The F statistic in a completely randomized ANOVA is the ratio of a. MSTR/MSE b. MST/MSE c. MSE/MSTR d. MSE/MST

a. MSTR/MSE

The correct relationship between SST, SSR, and SSE is given by a. SSR = SST - SSE b. SSR = SST + SSE c. SSE = SSR - SST d. None of these alternatives is correct

a. SSR = SST - SSE

In a residual plot against x that does not suggest we should challenge the assumptions of our regression model, we would expect to see a. a horizontal band of points centered near zero b. a widening band of points c. a band of points having a slope consistent with that of the regression equation d. a parabolic band of points

a. a horizontal band of points centered near zero

In regression analysis, the variable that is being predicted is the a. dependent variable (y) b. intervening variable c. independent variable (x) d. None of these answers is correct.

a. dependent variable (y)

SSE cab never be a. larger than SST b. smaller than SST c. equal to 1 d. equal to zero

a. larger than SST

A least squares regression line (Trend line) a. may be used to predict a value of y if the corresponding x value is given b. implies a cause-effect relationship between x and y c. can only be determined if a good linear relationship exists between x and t d. all of these answers are correct

a. may be used to predict a value of y if the corresponding x value is given

A multiple regression model has a. more than one independent variable b. only one independent variable c. at least 2 dependent variables d. more than one dependent variable

a. more than one independent variable

The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is the a. residual b. standard error c. variance d. prediction interval

a. residual

Coefficient of Determination r2 must be a.Between 0 and 1 b.Between -1 and 0 c.Between -1 and 1

a.Between 0 and 1

Which of the following is correct? a.SST = SSR + SSE b.SSR = SSE + SST c.SSE = SSR + SST d.SST = (SSR)2

a.SST = SSR + SSE

If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on this data is a. 0 b. 1 c. either 1 or -1, depending upon whether the relationship is positive or negative d. could be any value between -1 and 1

b. 1

If the coefficient of determination is equal to 1, then the coefficient of correlation a. must also be equal to 1 b. can be either -1 or +1 c. can be any value between -1 to +1 d. must be -1

b. can be either -1 or +1

In the ANOVA, treatment refers to a. experimental units b. different levels of a factor c. a factor d. applying antibiotic to a woud

b. different levels of a factor

An experimental design that permits statistical conclusions about two or more factors is a a. randomized block design b. factorial design c. completely randomized design d. randomized design

b. factorial design

When each data value in one sample is matched with a corresponding data value in another sample, the samples are known as a. corresponding samples b. matched samples c. independent samples d. None of these alternatives is correct.

b. matches samples

If the coefficient of correlation is a positive value, then the slope of the regression line a. None of these answers is correct b. must also be positive c. can be either negative or positive d. can be zero

b. must also be positive

The number of times each experimental condition is observed in a factorial design is known as a. partition b. replication c. experimental condition d. factor

b. replication

The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is the a. standard error b. residual c. prediction interval d. variance

b. residual

The equation that describes how the dependent variable (y) is related to the independent variable (x) is called a. the correlation model b. the regression model c. correlation analysis d. none are correct

b. the regression model

In a multiple regression model, the variance of the error term ε is assumed to be a. -1 b. the same for all values of the dependent variable c. 0 d. the same for all values of the independent variable

b. the same for all values of the dependent variable

In a simple regression analysis (where y is a dependent and x an independent variable), if the slope b1 is positive, then a. if x is increased, y must also decrease b. there is a positive correlation between x and y c. None of these answers is correct d. there is a negative correlation between x and y

b. there is a positive correlation between x and y

A variable that takes on the values of 0 or 1 and is used to incorporate the effect of qualitative variables in regression model is called a. an interaction b. a constant variable c. a dummy variable d. none

c. a dummy variable

A variable that cannot be measured in terms of how much or how many but instead is assigned values to represent categories is called a. an interaction b. a constant variable c. a qualitative variable

c. a qualitative variable

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 a. main effect b. replication c. interaction d. none is correct

c. interaction

In regression analysis, the variable that is being predicted a. must have the same units as the variable doing the predicting b. is the independent variable c. is the dependent variable d. usually is denoted by x

c. is the dependent variable

In multiple regression analysis, the correlation among the independent variables is termed a. homoscedasticity b. linearity c. multicollinearity d. adjusted coefficient of determination

c. multicollinearity

Regression analysis is a statistical procedure for developing a mathematical equation that describes how a. one independent and one or more dependent variables are related b. several independent and several dependent variables are related c. one dependent and one or more independent variables are related d. none are correct

c. one dependent and one or more independent variables are related

If we are interested in testing whether the proportion of items in population 1 is larger than the proportion of items in population 2, the a. null hypothesis should state P1 - P2 < 0 b. null hypothesis should state P1 - P2 > 0 c. alternative hypothesis should state P1 - P2 > 0 d. alternative hypothesis should state P1 - P2 < 0

c.alternative hypothesis should state P1 - P2 > 0

When an analysis of variance is performed on samples drawn from K populations, the mean square between treatments (MSTR) is a. SSTR/nt b. SSTR/(nt-1) c. SSTR/k d. SSTR/(k-1) e. none is correct

d. SSTR/(k-1)

The variable of interest in an ANOVA procedure is called a. a partition b. a treatment c. either a partition or a treatment d. a factor

d. a factor

In regression analysis if the dependent variable is measured in dollars, the independent variable a. must also be in dollars b. must be in some units of currency c. can be any units d. cannot be in dollars

d. cannot be in dollars

In a simple linear regression, r^2 is the a. estimated regression equation b. coefficient of correlation c. sum of the squared residuals d. coefficient of determination

d. coefficient of determination

If the coefficient of correlation is a negative value, then the slope of the regression line a. must also be positive b. can be either negative or positive c. can be zero d. must also be negative

d. must also be negative

If the coefficient of correlation is a negative value, then the coefficient of determination a. must also be negative b. must be zero c. can be either negative or positive d. must be positive

d. must be positive

In a simple regression analysis (where y is a dependent and x an independent variable), if the y intercept is positive, then a. there is a positive correlation between x and y b. there is a negative correlation between x and y c. if x is increased, y must also increase d. none are correct

d. none are correct

if there is a very strong correlation between two variables, then the coefficient of correlation must be a. much larger than 1, if the correlation is positive b. much smaller than 1, if the correlation is negative c. either much larger than 1 or much smaller than 1 d. none are correct

d. none are correct

In multiple regression analysis, a. there can be a any number of dependent variables but only one independent variable b. there just be only one independent variable c. the coefficient of determination must be larger than 1 d. there can be several independent variables, but only one dependent variable

d. there can be several independent variables, but only one dependent variable

In regression analysis, the independent variable is a. used to predict the dependent variable b. None of these answers is correct. c. used to predict other independent variables called the intervening variable d. used to predict the dependent variable

d. used to predict the dependent variable

When developing an interval estimate for the difference between two sample means, with sample sizes of n1 and n2, a. n1 must be equal to n2 b. n1 must be smaller than n2 c. n1 must be larger than n2 d. n1 and n2 can be of different sizes,

d.n1 and n2 can be of different sizes,