Question 1

The following are all terms associated with a t test, except:&#10;A) Significance level.&#10;B) Correlational coefficient.&#10;C) Sample mean.&#10;D) Null hypothesis.

Accepted Answer

The correlational coefficient is not associated with a t test. It is a measure of the strength and direction of the linear relationship between two variables, but it is not used in a t test. The other options - significance level, sample mean, and null hypothesis - are all key components of a t test.

Question 2

SPSS Statistics displays the following outputs for a t test:&#10;A) Model Summary&#10;B) One-Sample Statistics&#10;C) Coefficients&#10;D) ANOVA

Accepted Answer

One-Sample Statistics output is specific to t-tests and displays sample size, mean, standard deviation, and standard error for the tested variable. Model Summary, Coefficients, and ANOVA outputs are not necessary for t-tests.

Question 3

Use the following statistic to determine the statistical significance of the single sample mean: A) ANOVA Significance B) R² Linear value C) One-Sample Test Significance D) Standard Error of the Estimate

Accepted Answer

The One-Sample Test Significance is used to determine the statistical significance of a single sample mean. ANOVA Significance tests for differences between group means, R² Linear value is not a valid statistical term, and Standard Error of the Estimate measures the variability of a regression line.

Question 4

Use the following SPSS Statistics tool to calculate statistical significance:&#10;A) Linear Compare&#8230;&#10;B) Descriptive Statistics&#8230;&#10;C) Compare Means&#8230;&#10;D) Chart Editor&#8230;

Accepted Answer

The Compare Means tool is the best choice for calculating statistical significance as it allows us to compare means between two or more groups and perform statistical tests such as t-tests and ANOVA to determine if the differences between the means are statistically significant. The other tools do not provide the same level of analysis for determining statistical significance.

Question 5

What hypothesis is being tested when using a t test?&#10;A) Null hypothesis&#10;B) Test hypothesis&#10;C) Data-based hypothesis&#10;D) Sample mean hypothesis

Accepted Answer

When using a t-test, we are testing the null hypothesis, which states that there is no difference between the means of two populations. The alternative hypothesis, which is the hypothesis we want to support if the null hypothesis is rejected, is the test hypothesis.

Question 6

A t test requires one variable at the scale level.

Accepted Answer

A t-test requires the dependent variable to be measured at the interval or ratio level, which are both considered scale levels of measurement.

Question 7

A t test compares the sample mean to a test value.

Accepted Answer

A t test compares the sample mean to a test value, usually a hypothesized population mean or a target value.

Question 8

A significance value of .002 indicates a statistically significant finding at the .001 level.

Accepted Answer

A significance value of .002 indicates a statistically significant finding at the .01 level but not at the stricter .001 level.

Question 9

In research reports, you should mention information about the null hypothesis.

Accepted Answer

It is important to mention information about the null hypothesis in research reports in order to provide transparency and allow for future replication and verification of the findings.

Question 10

A negative t statistic demonstrates greater statistical significance.

Accepted Answer

A negative t statistic indicates that the sample mean is significantly lower than the population mean, thus providing greater evidence that the null hypothesis is false. Therefore, it demonstrates greater statistical significance.

Deck 12: The T-Test for a Single Sample Mean