Question 1

When you report only on the number of clients served and the average time of service provided to these clients in your agency, you are conducting:

Accepted Answer

Reporting only on the number of clients served and the average time of service provided is a descriptive study because it is describing the characteristics of the clients served and the services provided without attempting to explain or evaluate the effectiveness of the services.

Question 2

Reporting range, proportion, mean, mode, and median constitute:

Accepted Answer

Reporting range, proportion, mean, mode, and median are all basic descriptive statistics used to summarize and describe a data set. They do not involve any inference or testing of hypotheses, and they do not examine relationships between variables (which would be correlational or inferential statistics).

Question 3

The purpose of the study, to a large extent, determines the client characteristics you most need to describe. But you are normally expected to report on:

Accepted Answer

Basic demographic variables such as gender, age, and race are important to describe in any study as they provide important information about the characteristics of the sample and help to understand how the results may generalize to other populations. However, the other options (A, C, and D) may be relevant depending on the specific purpose of the study.

Question 4

Case level data implies that:

Accepted Answer

Case level data implies that you have data on each of the variables of your study for each subject in your study. This means that you have complete information on every variable for every subject.

Question 5

When you code the variable of religious affiliation, and when you assign codes such as Muslims = 3, Christians = 2, and Buddhists = 3, these codes are assigned:

Accepted Answer

The codes are assigned to distinguish the people in the study in regard to their religious affiliation, rather than to assert any hierarchy or to assign relative values. Assigning codes in this manner treats the variable as nominal or categorical rather than interval-level.

Question 6

Testing a hypothesis is a domain of:

Accepted Answer

Testing a hypothesis is a complex process that falls under the domain of inferential statistics. Inferential statistics deals with drawing conclusions and making predictions about a population based on sample data, which is exactly what hypothesis testing aims to do.

Question 7

Descriptive statistics relate to:

Accepted Answer

Descriptive statistics are used to summarize and describe the features of a dataset, which typically pertains to the study sample.

Question 8

The need to use inferential statistics is because:

Accepted Answer

Inferential statistics are used to make generalizations about a population based on a sample. Therefore, the goal is to estimate the likelihood that the findings in the sample apply to people not in the study sample. Option A is not entirely accurate as it mentions "relevant to the sample" instead of "representative of the population". Option B is not a goal of inferential statistics but rather descriptive statistics. Option D is not entirely accurate as summarizing variables can also be a goal of descriptive statistics.

Question 9

In general, with regard to parametric and nonparametric statistics:

Accepted Answer

Parametric statistics require assumptions about the underlying distribution of the data, such as normality, and are best suited for continuous variables measured at the interval or ratio level. Non-parametric statistics do not make these assumptions and are better suited for categorical, ordinal, or skewed data. Therefore, non-parametric statistics are used for nominal and ordinal data.

Question 10

With regard to the pie chart:

Accepted Answer

Pie charts are most effective when there are fewer categories, making it easier for viewers to compare the parts to the whole visually.

Question 11

The cumulative frequency is:

Accepted Answer

The cumulative frequency is the total number of observations that fall at or below a certain score or category in an ordinal variable. This means that it includes the number of people in a specific category and the number of people in categories that come before it in the hierarchy. Therefore, the best choice is D.

Question 12

A variable is something that is constant.

Accepted Answer

A variable is something that can change or take on different values. It is not constant.

Question 13

It is important to know the level of measurement because different statistical tests make the assumption that the variables in the analysis are measured at a given level.

Accepted Answer

The level of measurement determines what statistical tests can be used for analysis. For example, nominal variables can only be analyzed using non-parametric tests while interval and ratio variables can be analyzed using parametric tests. Therefore, it is important to know the level of measurement in order to choose the appropriate statistical test.

Question 14

Variables like gender and ethnicity have categories but are not recorded in any way that is numerical in nature and yet central tendencies like mean can be computed.

Accepted Answer

Central tendencies such as mean can only be computed for numerical data. Categorical variables such as gender and ethnicity cannot be used for mean calculation as they do not have a numerical value.

Question 15

You can compute the average for variables such as age when measured in actual number of years.

Accepted Answer

The average can be computed for variables that involve actual number measurements, such as age when measured in years.

Question 16

A researcher cannot treat a nominal variable as though it is measured at the ordinal level.

Accepted Answer

Nominal variables are categorical variables where there is no natural order or ranking to the categories. Ordinal variables, on the other hand, are categorical variables where the categories have a natural order or ranking. Treating a nominal variable as though it is measured at the ordinal level could result in incorrect analysis and conclusions.

Question 17

Descriptive statistics include frequencies, proportions, range, mean, median, and standard deviation.

Accepted Answer

Descriptive statistics refer to the methods used to summarize and describe a set of data, such as how often certain values appear (frequencies), the proportion of values that fall into certain categories (proportions), the spread between the smallest and largest values (range), the typical or average value (mean or median), and the variability of the data (standard deviation).

Question 18

The value of p helps us determine the probability that our data can be explained just by chance.

Accepted Answer

The p-value is used to calculate the probability that our data can be explained by chance. A low p-value indicates that the probability of chance is low, and we can reject the null hypothesis. Conversely, a high p-value indicates that the probability of chance is high, and we cannot reject the null hypothesis.

Question 19

We have to deal with statistical significance when we do not compare our sample to other people because we are not making any inferences about the ways in which our sample is or not different from a larger population of sample from which our sample was drawn.

Accepted Answer

Statistical significance is still relevant when we analyze a single sample because it helps us determine if the observed effects or differences in our sample are likely due to chance or if they reflect true differences or relationships within the population from which the sample was drawn.

Question 20

One of the assumptions of parametric statistics is that the data are not normally distributed.

Accepted Answer

One of the assumptions of parametric statistics is that the data are normally distributed. If the data are not normally distributed, non-parametric statistics may be more appropriate.

Quiz 4: Using Descriptive Statistics to Describe Your Study Sample