Question 1

The larger the number of data points, the easier it is to detect intervention effects.

Accepted Answer

A larger number of data points can provide a more accurate representation of trends and variability, making it easier to detect any changes or effects due to interventions.

Question 2

The chi-square approach can be used with auto-correlated data.

Accepted Answer

The chi-square approach assumes that observations are independent, and auto-correlated data violate this assumption because observations are not independent from each other.

Question 3

When the results of performing several measures of statistical significance (such as those listed above) differ, one simply takes the most powerful among these tests and assumes that this answer is the most nearly correct one of the group.

Accepted Answer

Choosing the most powerful test does not guarantee the most accurate result because the assumptions, applicability, and context of each test vary. The differences in results may indicate violations of assumptions or the influence of outliers, and each test's suitability must be considered in the context of the specific data and research question.

Question 4

The X-Moving Range-chart (the three-standard-deviation-band approach) is useful with small numbers of data.

Accepted Answer

The X-Moving Range-chart is designed for monitoring process variability when data is collected in small subgroups or individual observations, making it suitable for situations with small numbers of data.

Question 5

The t-test is a very powerful measure of statistical significance which can be calculated by hand or with a simple calculator, as well as by a computer program.

Accepted Answer

The t-test is a statistical test used to compare the means of two groups and can be calculated manually using formulas, with a calculator, or using statistical software.

Question 6

The C-Chart and the X-mR-Chart are both types of:&#10;A) Chi-square&#10;B) SPC's&#10;C) Proportion/Frequency Approaches&#10;D) CDC's

Accepted Answer

The C-Chart and the X-mR-Chart are both types of Statistical Process Control (SPC) charts used to monitor different types of processes or outputs within a manufacturing or production environment.

Question 7

The proportion/frequency approach can be used with dichotomous data.

Accepted Answer

The proportion/frequency approach is suitable for analyzing dichotomous data, which involves two possible outcomes or categories, by calculating the proportion or frequency of occurrences in each category.

Question 8

The chi square has a long tradition of use with single-system designs, and is, therefore, one of the safest statistics to use.

Accepted Answer

The chi-square test is primarily used for categorical data to test relationships between variables, not specifically for single-system designs, which often require different statistical methods tailored to their unique data structures and objectives.

Question 9

The randomization test is used to compensate when it is impossible to assign treatments randomly.

Accepted Answer

The randomization test is a statistical procedure used to test the null hypothesis by comparing the observed test statistic to the distribution of test statistics generated by randomly reallocating the observed data among the groups. It does not compensate for the inability to assign treatments randomly; instead, it assesses the significance of the observed data under the assumption of the null hypothesis.

Question 10

The CDC approach has been shown to be useful even with data that are positively auto- correlated up to an autocorrelation of .50.

Accepted Answer

The CDC (Case Detection Control) approach can effectively handle data with positive autocorrelation up to an autocorrelation of .50, as it is designed to identify and control for patterns within the data, including those caused by autocorrelation.

Deck 22: Tests of Statistical Significance for Single-System Designs