Qba Final

Front 1

If two independent large samples are taken from two populations, the sampling distribution of the difference between the two sample means

Back 1

can be approximated by a normal distribution

Front 2

An estimate of the variance of a population based on the combination of two sample results is known as the

Back 2

pooled variance estimate

Front 3

The pooled variance is appropriate whenever the two populations

Back 3

are normally distributed and have equal variances

Front 4

When each data value in one sample is matched with a corresponding data value in another sample, the samples are known as

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matched samples

Front 5

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

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overall sample mean

Front 6

The F ratio in a completely randomized ANOVA is the ratio of

Back 6

MSR/MSE

Front 7

The variable of interest in an ANOVA procedure is called

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a factor

Front 8

In the ANOVA, treatment refers to

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different levels of a factor

Front 9

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

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completely randomized design

Front 10

The EPA takes a random sample of 6 readings for each city and find the mean and variance. The populations are assumed to be normal with unknown but equal variances. The EPA should use a

Back 10

t test for difference in two means with independent data (pooled t test)

Front 11

the mean square is the sum of squares divided by

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its corresponding degrees of freedom

Front 12

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

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interaction

Front 13

the number of times each experimental condition is observed in a factorial design is known as

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replication

Front 14

assumptions of analysis of variance do not include

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equality of means

Front 15

when variances of two independent samples are combined and S^2 is computed, the S^2 is referred to as

Back 15

the pooled estimator of o^2

Front 16

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

Back 16

two or more populations are equal

Front 17

in testing the difference between the means of two normally distributed populations using independent random samples, the pooled estimate of the variance is used if

Back 17

population variances are assumed to be equal

Front 18

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

Back 18

one dependent and one or more independent variables are related

Front 19

A procedure used for finding the equation of a straight line which provides the best approximation for the relationship between the independent and dependent variables is the

Back 19

least squares method

Front 20

Application of the least squares method results in values of the y intercept and the slope which minimizes the sum of the squared deviations between the

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observed values of the dependent variable and the estimated values of the dependent variable

Front 21

Larger values of r2 imply that the observations are more closely grouped about the

Back 21

least squares line

Front 22

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?

Back 22

F test

Front 23

If the coefficient of determination is equal to 1, then the coefficient of correlation

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can be -1 or +1

Front 24

If the coefficient of determination is a positive value, then the regression equation

Back 24

could have either a positive or a negative slope

Front 25

If the coefficient of correlation is 0.8, the percentage of variation in the dependent variable explained by the variation in the independent variable is

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64%

Front 26

In regression analysis, if the dependent variable is measured in dollars, the independent variable

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can be any units

Front 27

If the coefficient of correlation is a positive value, then the slope of the regression line

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must also be positive

Front 28

If the coefficient of correlation is a negative value, then the coefficient of determination

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must be positive

Front 29

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

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1

Front 30

A multiple regression model has

Back 30

more than one independent variable

Front 31

Compared to the confidence interval estimate for a particular value of y (in a linear regression model), the interval estimate for an average value of y will be

Back 31

narrower

Front 32

A variable that can not be measured in terms of how much or how many but instead is assigned values to represent categories is called

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a qualitative variable

Front 33

the error term is the difference between an individual value of the dependent variable and the corresponding mean value of the dependent variable...t/f

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false

Front 34

the point estimate of the variance in a regression model is

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MSE

Front 35

what measures the strength of the linear relationship between the dependent and the independent variable

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correlation coefficient

Front 36

what is a violation of one of the major assumptions of the simple regression model?

Back 36

as the value of x increases, the value of the error term also increases

Front 37

the relationship between the dependent variable and the independent variable is stronger when the r^2 is __ and the s (standard error) is __

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higher, lower

Front 38

in a regression model, a value of the error term depends upon other values of the error term...t/f

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false

Front 39

when using a multiple regression model, we assume that error terms (residuals) are distributed according to

Back 39

normal distribution

Front 40

the multiple coefficient of determination is the __ divided by the total variation

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explained variation

Front 41

the residual is the difference between the observed value of the dependent variable and the predicted value of the dependent variable...t/f

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true

Front 42

in a simple linear regression model, the coefficient of determination not only indicates the strength of the relationship between independent and dependent variable, but also shows whether the relationship is positive or negative...t/f

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false

Front 43

when using simple linear regression, we would like to use confidence intervals for the __ and prediction intervals for the __ at a given value of x

Back 43

mean y-value, individual y-value

Front 44

in a simple linear regression analysis, the correlation coefficient and the slope always have the same sign...t/f

Back 44

true

Front 45

what are assumptions of the error terms in a simple linear regression model

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errors are normally distributed, error terms have a mean of zero and have a constant variance

Front 46

if all data points fell on a straight line, SSE would equal __ and r would equal __

Back 46

0, -1 or 1

Front 47

a t-test is used when testing the significance of an individual independent variable...t/f

Back 47

true

Front 48

if it is desired to include marital status in a multiple regression model by using the categories: single, married, separated, divorced, widowed, what will be the effect on the model?

Back 48

four more independent variables will be included

Front 49

A nonparametric method for determining the differences between two populations based on two matched samples where only preference data is required is the

Back 49

wilcoxon signed rank test

Front 50

Statistical methods that require assumptions about the population are known as

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parametric

Front 51

The Spearman rank-correlation coefficient is

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a correlation measure based on rank-ordered data for two variables

Front 52

A parameter of the exponential smoothing model which provides the weight given to the most recent time series value in the calculation of the forecast value is known as the

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smoothing constant

Front 53

A goodness of fit test is always conducted as a

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upper tail test

Front 54

A statistical test conducted to determine whether to reject or not reject a hypothesized probability distribution for a population is known as a

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goodness of fit test

Front 55

The time series component, which reflects a regular, multi-year pattern of being above and below the trend line is

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cyclical

Front 56

The time series component that reflects variability due to natural disasters is called

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irregular

Front 57

the smoothing constant is a number that determines how much weight it is attached to each observation...t/f

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true

Front 58

the sampling distribution for a goodness of fit test is

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the chi-square distribution

Front 59

a restaurant has been experiencing higher sales during the weekends compared to the weekdays. Daily restaurant sales patterns for this restaurant over a week are an example of what component of a time series

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seasonal

Front 60

the time series component that reflects variability during a single year is called

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seasonal

Front 61

one use of the chi-square goodness of fit test is to determine if specified probabilities in the null hypothesis is correct...t/f

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true

Front 62

in a contingency table, when all the expected frequencies equal the observed frequencies the calculated chi-squared statistic equals 0...t/f

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true

Front 63

a group of observations measured at successive time intervals is known as

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a time series

Front 64

which nonparametric method requires that we carry out a paired difference experiment

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wilcoxon signed rank test

Front 65

one measure of the accuracy of a forecasting model is

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the mean square error

Front 66

when we carry out a chi-square test of independence, the expected frequencies are based on the null hypothesis...t/f

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true

Front 67

exponential smoothing is a forecasting method that applies equal weights to the time series observations...t/f

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false

Front 68

when deseasonalizing a time series observation the actual time series observation is divided by its seasonal factor...t/f

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true

Front 69

statistical methods that generally require very few, if any, assumptions about the population distribution are known as

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nonparametric

Front 70

the time series component that reflects gradual variability over a long time period is called

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a trend

Front 71

if data for a time series analysis is collected on an annual basis only, which component may be ignored

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seasonal

Front 72

when using the chi-square goodness of fit test, if the value of the chi-square statistic is large enough, we reject the null hypothesis...t/f

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true

Front 73

the level of measurement that is simply a label for the purpose of identifying an item is

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nominal measurement

Front 74

statistical methods that generally require the assumptions that population distributions are normal are

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parametric