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The regression model

The equation that describes how the dependent variable (y) is related to the independent variable (x) is called

Qualitative variable

a variable that cannot be measured in numerical terms is called a

Influential Observation

An observation that has strong effect on the regression results is called

P-value

In a goodness of fit test, Excels CHISQ.DIST.RT function returns a

Outlier

A data point (observation) that does not fit the trend shown by the remaining data is called

Correlation Coefficient

A measure of the strength of the linear relationship between two variables is the

A Statistic

A numerical measure from a sample, such as a sample mean, is known as

Sample

A subset of a population selected to represent the population is a

Factor

A term that means the same as the term "variable" in an ANOVA procedure is

In both tails of the sampling distribution

A two-tailed test is a hypothesis test in which the rejection region is

A true null hypothesis is rejected

A type 1 error is committed when

Can be both qualitative & quantitative

All the variables in a multiple regression analysis

Observed values of the dependent variable and the predicted values of the dependent variable

Application of the least squares method result in values of the y-intercept and the slow that minimizes the sum of the squared deviations between the

Value of the coefficient of determination increases

As the goodness of fit for the estimate regression equation increases, the

The value of the multiple coefficient of determination increases

As the goodness of fit for the estimated multiple regression equation increases

Normal Probability Distribution

As the sample size becomes larger, the sampling distribution of the sample mean approaches a

Influential

Data points having high leverage are often

Also not be rejected at the 1% level

If a hypothesis is not rejected at a 5% level of significance, it will

Horizontal band of points centered near 0

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

n-1

In determining an interval estimate of a population mean when sigma is unknown, we use t distribution with how many degrees of freedom

CHISQ.DIST

In excel which function is used to conduct a hypothesis test (using the p value) for a population variance

Multicollinearity

In multiple regression analysis, the correlation among the independent variables is termed

Accomodate curvilinear relationships between independent variables and dependent variable

In multiple regression, the general linear model can

Dependent Variable

In regression analysis the variable that is being predicted is the

Can be any units

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

X-axis of a scatter diagram

In regression analysis, the independent variable is typically plotted on the

Dependent Variable

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

Different levels of a factor

In the ANOVA, treatment refers to

Smaller p-values

More evidence against the null hypothesis is indicated by

One dependent variable and one or more independent variables are related

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

one dependent and one or more independent variable are related

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

Larger than SST

SSE can never be

Two or more populations are equal

The ANOVA procedure is a statistical approach for determining whether the means of

Confidence Level

The ability of an interval estimate to contain the value of the population parameter is described by the

the number of independent variables

The adjusted multiple coefficient of determination is adjusted for

Sample Size

The degrees of freedom associated with a t distribution are a function of the

Central Limit Theorem

The fact that the sampling distribution of the sample mean can be approximated by a normal probability distribution whenever the sample size is large is based on

Its corresponding degrees of freedom

The mean square is the sum of squares divided by

Coefficient of Determination

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

Value greater than 0

The random variable for a chi square distribution may assume any

X Bar

The sample statistic s is the point estimator of

Chi-Square Distribution

The sampling distribution for a goodness of fit test is the

Chi Square

The sampling distribution used when making inferences about a single populations variance

P-value & Critical Value

Two approaches to drawing a conclusion in a hypothesis test are

An F test

Used to determine whether an additional variable makes a significant contribution to a multiple regression model

Matched Samples

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

a multiple regression model

a regression model in which more than one independent variable is used to predict the dependent variable is called

Goodness of fit test

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

A residual

the difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is called

Point estimate & Margin of error

the general form of an interval estimate of a population mean or population proportion is the BLANK plus or minus the BLANK

Number of rows minus 1 times the number of columns minus 1

the number of degrees of freedom for the appropriate chi-square distribution in a test of independence is

t distribution should be used when

the sample standard deviation is used to estimate the population standard deviation

sigma squared

the symbol for the variance of the population is

Best Subsets Regression

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


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