Question 1

The chi-square test is a test to determine whether the difference
between two proportions is greater than would be expected because of sampling
error.

Accepted Answer

The chi-square test is a statistical test used to determine whether there is a significant difference between observed frequencies and expected frequencies in a contingency table. It is commonly used to analyze categorical data and test for independence or association between two variables. It is not specifically used to compare proportions.

Question 2

Researchers cannot perform statistical testing on nominal data.

Accepted Answer

Nominal data can be analyzed using statistical tests that are designed for categorical data, such as the Chi-square test for independence, to determine if there are significant associations between categories.

Question 3

The issue of whether certain measurements are different from one another is central to many questions of critical interest to marketing managers.

Accepted Answer

Yes, the issue of whether certain measurements are different from one another is central to many questions of critical interest to marketing managers. For example, they may need to compare sales figures for different products, customer satisfaction ratings for different service providers, or demographic characteristics of customer segments. In order to make informed decisions based on these measurements, they need to know whether any observed differences are statistically significant, or whether they could have arisen by chance.

Question 4

Researchers cannot perform statistical testing unless the sample size is at least 30.

Accepted Answer

There is no set minimum sample size required for statistical testing. The appropriate sample size depends on various factors including the research question, population size, and the level of desired precision.

Question 5

Big data does not mean "good" data.

Accepted Answer

Just because there is a large amount of data does not necessarily mean that it is accurate, relevant, or useful. It is important to carefully analyze and interpret the data to ensure its quality and usefulness.

Question 6

A p value of .285 would be acceptable for a research analyst to reject the null hypothesis.

Accepted Answer

A p-value of .285 is not considered statistically significant and does not provide enough evidence to reject the null hypothesis. Typically, a p-value less than .05 is required for rejecting the null hypothesis.

Question 7

The chi-square test enables the research analyst to determine whether an observed pattern of frequencies corresponds to,or fits,an "unexpected pattern."

Accepted Answer

The chi-square test enables the research analyst to determine whether an observed pattern of frequencies corresponds to, or fits, an "expected pattern," not an "unexpected pattern."

Question 8

If the alternative hypothesis is supported,the researcher concludes there are significant differences in the phenomenon being measured.

Accepted Answer

When the alternative hypothesis is supported, it means that there is evidence to suggest that there are significant differences in the phenomenon being measured, leading to the rejection of the null hypothesis. Therefore, the conclusion would be that there are significant differences in the phenomenon being studied.

Question 9

A consultant has a random sample of 400 usable responses in a database.Included are the following questions: Household Income Category: $ \begin{array}{ll}\text { (1) } \$ 0 \text { to } \$ 24,999 & \text { (2) } \$ 25,000 \text { to } \$ 49,999\end{array} $ (3) $ \$ 50,000 $ to $ \$ 99,999 $ (4) $ \$ 100,000 $ and over Average Weekly Soft Drink Consumption:ـ___________________ The consultant wants to determine if there are any statistically significant differences in average weekly soft drink consumption by income category.What statistical test should be applied to give the consultant the information he needs?

Accepted Answer

The answer of A consultant has a random sample of...

Question 10

Failing to reject the null hypothesis is the same as accepting the null hypothesis.

Accepted Answer

Failing to reject the null hypothesis does not mean that we accept it. Rather, it means that we do not have enough evidence to reject it at the given level of significance. The null hypothesis may or may not be true, but we cannot directly accept it based on our failure to reject it.

Question 11

There are fewer statistics available for analyzing nominal data than there are for analyzing metric data.

Accepted Answer

Nominal data, being categorical and not based on any inherent order or scale, limits the types of statistical analyses that can be performed, unlike metric (quantitative) data, which can be analyzed using a wider range of statistical methods due to its numerical nature.

Question 12

Researchers very rarely know the population mean.

Accepted Answer

It is rare for researchers to have data on an entire population, so they seldom know the true population mean. Rather, they use sample statistics to estimate population parameters.

Question 13

Suppose a client wants to evaluate average weekly miles jogging by males and females.Initially,the consultant thinks a t-test would be the preferred method of analysis.However,the client wants to know where the differences exist among short,medium and long mileage joggers.What will the consultant have to do to satisfy his/her client?

Accepted Answer

The answer of Suppose a client wants to evaluate average...

Question 14

A consultant has collected 700 usable responses via a probability sample concerning political opinions.After analyzing each respondent's political ideology,he/she divides the respondents into two groups,moderate liberals and moderate conservatives.Further,the consultant asks respondents the following:
How likely are you to vote for increasing property taxes in the next election?
(1)very unlikely	(2)somewhat unlikely	(3)undecided
(4)somewhat likely	(5)very likel 
The consultant wants to determine if the moderate conservatives differ significantly from moderate liberals concerning how they'll vote on the property tax issue in the next election.How should the data be analyzed?

Accepted Answer

The answer of A consultant has collected 700 usable responses...

Question 15

ANOVA is a statistical technique that permits the researcher to determine whether the variability among or across the independent sample means is greater than expected because of sampling error.

Accepted Answer

This statement accurately represents the purpose and function of ANOVA.

Question 16

The smaller the p value,the smaller is the probability that the observed result occurred by chance.

Accepted Answer

This statement is true. A smaller p-value indicates stronger evidence against the null hypothesis and a smaller probability that the observed result occurred by chance. Typically, a p-value less than 0.05 is considered statistically significant, indicating a low probability of the observed result happening by chance.

Question 17

In the decision that the null hypothesis is accepted,there must be enough evidence in the data that the alternative hypothesis is correct.

Accepted Answer

In the decision that the null hypothesis is accepted, it means that there is not enough evidence in the data to reject the null hypothesis. However, it does not necessarily mean that the alternative hypothesis is correct. It simply means that there is not enough evidence to support the alternative hypothesis over the null hypothesis. Therefore, the statement "there must be enough evidence in the data that the alternative hypothesis is correct" is false.

Question 18

A Type I error involves rejecting the null hypothesis when it is,in fact,true.

Accepted Answer

A Type I error occurs when we reject the null hypothesis, assuming there is a significant difference, when in reality there is no significant difference and the null hypothesis is true.

Question 19

ANOVA is used to analyze the differences of more than 2 means.

Accepted Answer

ANOVA (Analysis of Variance) is a statistical method used to determine if there are any significant differences among the means of three or more groups. Therefore, it is used to analyze the differences of more than 2 means.

Question 20

Placing total reliance on significance testing is a good idea.

Accepted Answer

Placing total reliance on significance testing is not a good idea as it has certain limitations and drawbacks. Significance testing only tells us if a result is statistically significant or not, but it does not provide information about the magnitude or practical significance of the effect. It also assumes certain conditions which may not always hold true in real-world situations. Therefore, it is important to use other methods of data analysis and interpretation along with significance testing to make informed decisions.

Quiz 16: Statistical Testing of Differences and Relationships

The chi-square test is a test to determine whether the difference between two proportions is greater than would be expected because of sampling error.