BNAD 277

there is interaction between factors A and B

Alternative hypothesis when using F test statistic: MSAB/MSE

normal

As DF increases, the Chi-square becomes more like this distribution:

test > critical value, p-value < alpha

For a chi square test, what are the conditions for rejecting Ho based on p-value approach and the critical value approach

the sum of all the observations and then dividing them by the total number of observations

In an ANOVA test, how do we calculate the grand mean

estimate

In inferential statistics, sample variance is an ___________ for population variance

SSTR/(c-1)

In one-way ANOVA, the MSTR is calculated as

randomized block design

In two-way ANOVA, if units within each block are randomly assigned to each of the treatments, then the design of the experiment is referred to as a

u1=u2=u3=u4

Null hypothesis to test whether or not there is a difference between treatments A, B, C and D. A sample of 8 observations has been randomly assigned to the 4 treatments:

N

The sum of expected frequencies in a goodness of fit test always equals

1

The sum of expected probabilities in a goodness of fit test is always

independent

The trials in a multi-nominal experiment must be

between

Treatment refers to

True

True or false: one way ANOVA analysis does not require that all means differ from one another

for any number or pairwise comparisons

Tukey's HSD method ensures that the probability of a type 1 error equals alpha

0

a skewness coefficient of what indicates that data are symmetric about its mean

the variability of stock return differs from 10%

an example of conducting statistical inference using the population variance would be when we want to examine whether

No because 0.0701 > .05

at the 5% significance level, can we conclude that the column means differ?

p=.089 and alpha= .05 what do you do

do not reject the null since p-value was greater than alpha

goodness of fit

for a multinomial experiment, this test is used to determine whether the sample proportions differ significantly from the hypothesized population proportions

do not reject the null

if p-value is greater than alpha

reject the null

if p-value is smaller than alpha

Reject the Null

if the confidence interval does not include "0" when the hypothesized value is "0" you must:

type 1 error increases as the number of pairwise comparisons increases

on disadvantage of Fisher's LSD method is the probability of committing a

p>.1

p-value where value of F is 1.7 with df's 2 and 5

1 (area)

the area under the chi squared distribution

as degrees of freedom get larger

the chi square distribution tends to the normal distribution as the

F distribution

the one way ANOVA test is based on what distribution

2

the test statistic for the jarque-bera test for normality follows the chi square distribution with df equal to

error

within refers to

chi squared distribution

Statistical inference concerning the population variance is based on the

F Distribution

Testing for the difference of two population variances is based on this distribution:

normal distribution

The chi square distribution is derived from this distribution

3 SSA + SSB + SSE

The number of components that make up the SST for a two-way ANOVA without interaction:

2

The number of qualitative variables in a test for independence

pi = ei / n

formula for pi, given ei and n:

you reject the null

if your test statistic is larger than your critical value

you do not reject the null

if your test statistic is smaller than your critical value

Sum of weighted sample variances of each treatment

in a one-way ANOVA, the error sum of squares (SSE) is the

variability

inference concerning the ratio of two population variances is used to compare relative

true

true or false: Tukey's honestly significant differences HSD method can accommodate unbalanced data

true

true or false: the formula for the confidence interval for the population variance is valid only when the random sample is drawn from a normally distributed population

true

true or false: the null hypothesis for the jarque-bera test consists of the joint hypothesis that the skewness and kurtosis coefficient are both equal to zero

compares population means based on two categorical variables or factors

two way ANOVA

3

ANOVA will be used in Ch. 13 when at least this many populations are under consideration

not so, or all population means are not equal

Alternative hypothesis for a two-way ANOVA without interaction

4, 45

An ANOVA procedure is applied to data obtained from 5 samples where each sample contains 10 observations. The DF's for the critical value of F are this

Mean Squared Error

MSE stands for:

columns

Typically factor A refers to rows or columns in a Two-way ANOVA:

population variance

We've been concerned with using inferential stats as it concerns a central measure of location, the mean. In chapter 11 we are concerned with inferential stats as it concerns this

T distribution

When you conduct a Fisher Confidence interval for the difference between two population means, we use which distribution

two possible outcomes

a binomial experiment is a series of N identical trials of a random experiment where each trial has

as peaked as the normal distribution

a kurtosis coefficient of zero means that the distribution is

two

a two-way anova test simultaneously examines the effect of how many factors on the population mean

5 or more

for the chi-square test of normality, the expected frequencies for each interval must be

reject the null and conclude that not all population means are equal

in ANOVA testing, if the ratio of the between-treatment variability to within-treatment variability is significatnly greater than 1, then we

two qualitative variables

the chi-square test of contingency table is a test of independence for

chi squared distribution

the confidence interval for the population standard deviation uses the

the value of the test statistic depends on how the data are grouped

the criticism of the goodness of fit test for normality is that

MSA/MSE

in a two-way ANOVA, the F statistic that determines whether significant difference exist between the factor A means is calculated as

MSB/MSB

in a two-way ANOVA, the F statistic that determines whether significant difference exist between the factor B means is calculated as

the variability between sample means

in one way ANOVA, between treatments variability is based on

between treatments variability and within treatments variability

in one-way ANOVA, two independent estimates of the common population variance, o^2, are estimated. these estimates are commonly referred to as

a weighted sum of the sample variances of each treatment

in one-way ANOVA, within treatments variability is based on

mean and standard deviation

in order to express the competing hypothesis for a goodness of fit test for normality, we specify the populations

2 or 3

in two-way ANOVA test, how many null hypotheses are tested?

4 SST=SSA + SSB + SSAB + SSE

in two-way ANOVA with interaction, we partition the total sum of squares into how many distinct components

3 SST = SSA + SSB + SSE

in two-way ANOVA without interaction, we partition the total sum of squares SST into how many distinct components

reduces

performing a one-way ANOVA test, instead of performing a series of two sample t-tests does what to the risk of incorrectly rejecting the null hypothesis

observed and expected frequencies

the goodness of fit in the goodness of fit test depends on

if difference exists between the means of three or more populations

we use ANOVA to determine

Ho: the data are normal Ha: the data are not normal

what is the null and alternative hypothesis for the goodness of fit test

Ho: S=0 and K=0

what is the null hypothesis for the Jarque-Bera test for normality

there is no interaction between factors A and B

which is a null hypothesis is applicable for a two-way ANOVA test with interaction