ECON

By conducting numerous pairwise t-test comparisons on means, we inflate the risk of the Type ----- error.

1

A two-way ANOVA test simultaneously examines the effect of ----- factor(s) on the population mean.

2 or two

In two-way ANOVA with interaction, we partition the total sum of squares into ----- distinct components.

4

In a one-way ANOVA table, = MSTR/MSE.

F

True or false: The ANOVA test simultaneously determines whether differences exist between the population means and identifies those population means that may differ.

FALSE

In a two-way ANOVA, the Fdf1,df2 statistic that determines whether significant differences exist between the factor A means is calculated as --- /---

MSA/MSE

SSB/ r-1

MSB

In a one-way ANOVA table, = --- SSE/nT-c.

MSE

SEE/ nT-c-r+1

MSE

SSE/ rc(w-1)

MSE

The value of the test statistic for testing whether differences exist between the population means is computed as --- ---.

MSTR MSE

In two-way ANOVA with interaction, we partition the total sum of squares SST into the following components: - SSA and SSB - SSA, SSB, SSAB, and SSE - SSA, SSB, and SSE - SSAB and SSE

SSA, SSB, SSAB, and SSE

The formula for the mean square error (MSE) is equal to what? - SSE/nT - SSE×nT - SSE/(nT- c) - SSE×(nT- c)

SSE/(nT- c)

In two-way ANOVA without interaction, the error sum of squares (SSE) is calculated as ______. - SST - (SSA + SSB) - (SSA + SSB) -1 - SST - 1 - MSA - MSB

SST - (SSA + SSB)

True or false: The two-way ANOVA test can be conducted with or without examining the interaction of the two factors. t f

TRUE

- If the interaction between two factors is not significant, what are the next ANOVA tests to be done? - None. Gather more data instead. - None. The analysis is complete. - Tests about the population means of factor A and/or factor B - None. More sophisticated techniques such as regression analysis should be used next.

Tests about the population means of factor A and/or factor B

Which of the following is NOT an assumption for performing a one-way ANOVA? - The populations are normally distributed. - The population standard deviations are unknown but assumed equal. - The population correlation coefficients indicate a strong linear relationship. - The samples are selected independently.

The population correlation coefficients indicate a strong linear relationship.

As compared to Fisher's LSD method, which method is an improved multiple comparison technique? - mann whitney's - sharpe's - chebyshev's - tukey's hsd

Tukey's hsd

With two-way ANOVA, we are examining two factors, we use the notation SSA to capture the variability between the levels of factor ----- and SSB to capture the variability between the levels of factor -------.

a, b

df1 = c-1 df2 = nf-1 MSTR = the btwn treatements variance MSE = the within- treatments variance nT = total sample size

all correctly matched

In a completely randomized ANOVA design, if there are an equal number of observations in each sample, then the design is ----

balanced

Place the sources of variation from a one-way ANOVA table in the correct order. - total - within groups - btw groups

btwn groups within groups total

The ANOVA test assume the population standard deviations are unknown but ------.

equal

The ______ is a weighted sum of the sample variances of each treatments. - error sum of squares - sum of squares due to treatments - total sum of squares - grand mean

error sum of squares

In a two-way ANOVA test, the sum of squares for factor A is based on the sum of the squared differences between the mean for each level of factor A and the -----

grand mean

In a two-way ANOVA test, the sum of squares for factor B is based on the sum of the squared differences between the mean for each level of factor B and the ---- ----.

grand mean

The more means we compare, the more the Type I error becomes -----.

inflated, larger, bigger

A one-way analysis of variance (ANOVA) test compares ----- population based on one categorical variable or factor.

means

The one-way analysis of variance (ANOVA) test is used to determine if differences exist between the ----- of three or more populations.

means

---- is the within-treatments variance.

mse

---- is the between-treatments variance.

mstr

The ANOVA test assume the populations are ----- distributed.

normally / normal

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

reduces

Place the sums of squares from a one-way ANOVA table in the correct order. sst sstr sse

sstr sse sst

In one-way ANOVA, the error sum of squares (SSE) is the ---- - sum of the weighted sample variances of each treatment. - sum of the weighted squared differences between the samples mean and the grand mean. - sum of all observations in the data set divided by the total number of observations.

sum of the weighted sample variances of each treatment.

In one-way ANOVA, within-treatments variability is based --- --- on the each sample.

variability within

Fisher's least difference (LSD) method is applied - when the ANOVA test has not rejected the null hypothesis of equal population means. - since Tukey's HSD method inflates the risk of a Type I error. - when the ANOVA test has rejected the null hypothesis of equal population means.

when the ANOVA test has rejected the null hypothesis of equal population means.

One of the disadvantages of Fisher's least difference (LSD) method is that the probability of committing a - Type II error increases as the number of pairwise comparisons decreases. - Type I error increases as the number of pairwise comparisons decreases. - Type I error increases as the number of pairwise comparisons increases. - Type II error increases as the number of pairwise comparisons increases.

Type I error increases as the number of pairwise comparisons increases.

x bar bar is the symbol for the ----- .

grand mean

In ANOVA testing, if the ratio of the between-treatment variability to within-treatment variability is significantly greater than one, then we --- - do not reject the null hypothesis and conclude that all population means are equal - reject the null hypothesis and conclude that not all population means are equal - do not reject the null hypothesis and conclude that not all population means are equal - reject the null hypothesis and conclude that all means are equal

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