bnad
18. When using Fisher's least significant difference (LSD) method at some stated significance level, the probability of committing a Type I error increases as the number of: A. pairwise comparisons decreases B. pairwise comparisons increases C. sample size increases D. treatments decreases
B
A correlation coefficient r = -0.85 could indicate a: A. Very weak positive linear relationship. B. Very strong negative linear relationship. C. Very weak negative linear relationship. D. Very strong positive linear relationship.
B
One-Way ANOVA analyzes the effect of one factor on the population mean. It is based on a: A. randomized block design B. completely randomized design C. factorial design D. balanced incomplete block design
B
14. The variability due to chance, also known as within-treatments variability, is the estimate of 2 which is based on the: A. variability of the data across different samples B. consistency of the data within each sample C. variability of the data within each sample D. reliability of the data within each sample
C
If units with each block are randomly assigned to each of the treatments, then the design of the experiment is referred to as a: A. factorial design B. completely randomized design C. randomized block design D. balanced incomplete block design
C
13. If there are five treatments under study, the number of pairwise comparisons is: A. 15 B. 5 C. 20 D. 10
D
When the null hypothesis is rejected in an ANOVA test, Fisher's least significant difference method is superior to Tukey's honestly significant differences method to determine which population means differ.
False
f units within each block are randomly assigned to each of the treatments, then the design of the experiment is referred to as a completely randomized design.
False
n general, blocks are the levels at which we hold an integral factor fixed, so that we can measure its contribution to the variation within the samples.
False
When two factors interact, the effect of one factor on the population mean depends upon the specific value or level present for the other factor.
True
Compared to the sample correlation coefficient, the sample covariance is a better measure to gauge the strength of the linear relationship between two variables. True False
false
Each point in the scatterplot represents one observed value for one variable. True False
false
If two linear regression models have the same number of explanatory variables, a model with an R2 value of 0.45 is a better prediction model than a model with an R2 value of 0.65. True False
false
In testing the population correlation coefficient, the alternative hypothesis is . True False
false
Simple linear regression includes more than one explanatory variable. True False
false
The correlation coefficient can only range between 0 and 1. True False
false
The positive square root of the coefficient of determination in simple linear regression is always equal to the correlation coefficient. True False
false
The restricted model is a reduced model where we estimate the coefficients that are restricted under the null hypothesis. True False
false
In the simple linear regression model, 0 is the y-intercept of the line . True False
true
The term BLUE stands for Best Linear Unbiased Estimator.
true
The value 0.35 of a sample correlation coefficient indicates a weaker linear relationship than that of - 0.40. True False
true
In a two-way ANOVA test, how many null hypotheses are tested? A. 1 B. 1 or 2 C. 2 or 3 D. More than 3
C
Tukey's honestly significant differences (HSD) method uses Fishers least differences (LSD) method for pairwise comparisons. A. t values; studentized range values B. studentized range values; F values C. F values; t values D. studentized range values; t values instead of when compared to
D
Which of the following identifies the range for a correlation coefficient? A. Any value less than 1 B. Any value greater than 0 C. Any value between 0 and 1 D. None of the above
D
We use ANOVA to test for differences between population means by examining the amount of variability between the samples relative to the amount of variability within the samples.
True
If the interaction between two factors is not significant, the next tests to be done are: A. None, the analysis is complete. B. None, gather more data. C. Tests about the population means of factor A or factor B using two-way ANOVA without interaction. D. Tukey's confidence intervals.
c
21. One of the disadvantages of Fisher's least difference (LSD) method is that the probability of committing a: A. Type II error increases as the number of pairwise comparisons increases. B. Type I error increases as the number of pairwise comparisons decreases. C. Type II error increases as the number of pairwise comparisons decreases. D. Type I error increases as the number of pairwise comparisons increases.
dD
ANOVA is a statistical technique used to determine if differences exist between the means of two populations.
false
The sample correlation coefficient cannot equal zero. True False
false
A crucial assumption in a regression model is that the error term is not correlated with any of the explanatory variables. True False
true
Tukey's honestly significant differences (HSD) method ensures that the probability of a Type I error remains fixed irrespective of the number of: A. pairwise comparisons B. treatments C. replications within each treatment D. replications for each combination of factor A and factor B
A
Identify the assumption that is not applicable for a one-way ANOVA test. A. The populations are normally distributed B. The population standard deviations are not all equal C. The samples are selected independently D. The sample is drawn at random from each population
B
One-way ANOVA analyzes the effect of one factor on the population mean and it is based on a completely randomized design.
True
16. Between-treatments variability is based on a weighted sum of squared differences between the: A. population variances and the overall mean of the data set B. sample means and the overall mean of the data set C. sample variances and the overall mean of the data set D. population means and the overall mean of the data set
b
Another name for an explanatory variable is the dependent variable. True False
false
The alternative hypothesis for the test of joint significance is specified as: HA: At least two j 0.
false
A scatterplot can help determine if two variables are related in some systematic way.
true
The interaction test is performed before making any conclusions based on the tests for the main effects.
True
When using Fisher's LSD method at some stated significance level , the probability of committing a Type I error increases as the number of pairwise comparisons increases.
True
The test statistic for testing the individual significance is assumed to follow the t distribution with n - k - 2 degrees of freedom, where n is the sample size and k is the number of explanatory variables. True False
false
When some explanatory variables of a regression model are strongly correlated, this phenomenon is called serial correlation.
false
The between-treatments variability is the estimate of 2 which is based on the variability due to chance.
falses
A wavelike movement in residuals suggests positive serial correlation.
true
The value -0.75 of a sample correlation coefficient indicates a stronger linear relationship than that of 0.60. True False
true
The value 0.75 of a sample correlation coefficient indicates a stronger linear relationship than that of 0.60. True False
true
The simple linear regression model can be written in the form True False
false
15. If the amount of variability between treatments is significantly greater than the amount of variability within treatments, then: A. reject the null hypothesis of equal population means B. do not reject the null hypothesis of equal population means C.conclude that the ratio of between-treatments variability to within-treatments variability is significantly less than 1 D. perform further analysis using the two-way ANOVA with interaction
a
17. Fisher's least difference (LSD) method is applied when the: A. ANOVA test has not rejected the null hypothesis of equal population means B. ANOVA test has rejected the null hypothesis of equal population means C. Two-sample t test is not applicable D. None of the above
b
Which of the following is the correct interpretation of the Fisher's 100(1 - )% confidence interval for i - j? A.If the interval includes the value zero, the null hypothesis, that H0: i - j = 0, is rejected for at level of significance B.If the interval does not include the value zero, the null hypothesis, that H0: i - j = 0, is rejected at 100(1 - )% level of significance C.If the interval does not include the value zero, the null hypothesis, that H0: i - j = 0, is rejected at level of significance D.If the interval includes the value zero, the null hypothesis, that H0: i - j = 0, is rejected at 100(1 - )% level of significance
c
Which of these null hypotheses is applicable for a two-way ANOVA test with interaction? A. There is interaction between factors A and B. B. Factor A and factor B means differ. C. There is no interaction between factors A and B. D. Factor A and factor B means do not differ.
c
The term multicollinearity refers to the condition when the variance of the error term, conditional on x1, x2, xn, is the same for all observations. True False
false
Covariance can be used to determine if the linear relationship between two variables is positive or negative. True False
true
If in the multiple linear model the slope coefficient i is negative, it suggests an inverse (negative) relationship between the explanatory variable xi and the response variable. True False
true
The correlation coefficient could be considered as a "standardized covariance." True False
true
