Mass Media Research: An Introduction, 8th Edition Instructor’s Manual (стр. 7 )

The chapter introduces the term sample distribution—the distribution of some characteristic measured on an individual or other unit of analysis that were part of a sample. Additionally, the chapter introduces the notion of a sampling distribution—a theoretical probability distribution of all values of a variable for a given sample size.

The final part of the chapter discusses data transformation. Most statistical procedures are based on the assumption that the data are normally distributed. When some anomalies arise, researchers can attempt to transform the data to achieve normality. Data transformation can be possible by multiplying or dividing each score by a certain number, or taking the square root or log of the scores.

Exercises

Learn about statistical packages such as SPSS, SAS, or LISREL on the Internet. Try to find out the characteristics, history, price, and so on. Let students use Excel and SPSS and compare both tools’ functions

Practical Problems

Find the mean, mode, and median for these two data sets.

Data set A: 1, 2, 2, 3, 4, 5, 6, 3, 3, 5, 3, 3, 9, 10

Date set B: 10, 11, 11, 20, 29, 13, 13, 17, 13, 16, 18

Find range, sample variance, and standard deviation for the set of data.

5, 7, 7, 8, 9, 9, 9, 10, 11, 11, 19

Answers

Data set A Data set B

Mean = 4.21 Mean = 15.54

Mode = 3 Mode = 13

Median = 4.5 Median = 13

Range = 14

Sample variance = 13.07

Standard deviation = 3.62

Multiple Choice

A frequency distribution:

a)  Is an example of an inferential statistic

b)  Is used to display data

c)  Is the same thing as a frequency polygon

d)  Cannot be used with nominal data

On a histogram, the frequency of the scores is usually displayed on the:

a)  Horizontal axis

b)  Orthogonal axis

c)  Vertical axis

d)  Vertical and horizontal axis

Which statistic does not refer to the midpoint of the data?

a)  Mode

b)  μ (mu)

c)  Sigma

d)  Mean

One descriptive statistic is dispersion. Which of the following is not a measure of dispersion?

a)  Range

b)  Skewness

c)  Variance

d)  Standard deviation

Suppose that a mass media researcher wants to compare average time per day of TV viewing and newspaper reading in a group of college students. However, this researcher used a different instrument (5 point Likert scale for TV viewing & 7 point Likert scale for newspaper reading). What statistic would be appropriate to compare the average score of these media behaviors?

a)  Standard deviation

b)  Z-score

c)  Histogram

d)  Chi-square

A radio manager sampled 300 listeners and found that 30% of the sample was listening a certain program. What is the approximate.95 confidence interval estimate for the population mean? The population average lies between…

a)  33% and 37%

b)  20% and 24%

c)  10% and 15%

d)  25% and 35%

True/False

A frequency distribution is a table of the scores ordered according to magnitude and their frequency of occurrence. (T) The median is the score that occurs most frequently. (F) A small variance indicates that most of the scores in the distribution lie widely scattered from the mean. (F) To obtain a measure of dispersion that is calibrated in the same units as the original data (standard deviation), it is necessary to take the square root of the median. (F) The mean of a distribution of z-scores is always 1.0. (F)

Fill in the Blank

If a line is drawn from the midpoint of each interval at its peak along the y-axis to each adjacent midpoint/peak, the result graph is called a (frequency polygon). (Skewness) refers to the concentration of scores around a particular point on the x-axis. The amount that sample mean differs from the population mean is called the (sampling error). (Confidence interval) is an area within which there is a stated probability that the parameter will fall. When such anomalies arise, researchers can attempt to transform the data to achieve (normality).

Short Answer

1.  Discuss the difference among central tendency measures

2.  Discuss possible practical uses of the confidence interval (e. g., establishing norms for medical tests, IQ tests, etc.)

Chapter 11 - Hypothesis Testing

Overview

This chapter describes the importance of hypotheses testing in empirical research procedures. Hypothesis development in scientific research is important because the process refines and focuses research by excluding extraneous variables and permitting variables to be quantified. Scientists rarely begin a research study without a problem or a question to test. Without research questions or hypotheses, research proves to be a waste of time.

Researchers develop studies based on existing theory and are thus able to make predictions about the outcome of their work. Therefore, hypothesis development is usually the culmination of a rigorous literature review. Researchers should use hypotheses in scientific research to: 1) provide direction for a study; 2) eliminate trial-and-error research; 3) rule out intervening and confounding variables; and, 4) allow for quantification of variables. In addition, hypotheses should be: 1) compatible with current knowledge in the area; 2) logically consistent; 3) stated concisely; and, 4) testable.

The second half of the chapter emphasizes the concepts of null hypothesis, error, and power because hypotheses must be tested for statistical significance. In hypothesis testing, a researcher either rejects or fails to reject the null hypothesis that the statistical differences being analyzed are due to chance or random error. To determine the statistical significance of a research study, the research must set a probability level (significance level) against which the null hypothesis is tested. If the results of the study indicate a probability lower than this level, the researcher can reject the null hypothesis. If the research outcome has a high probability, the researcher fails to reject the null hypothesis. It is common practice in mass media research studies to set the probability level at.01 or.05, which means that either one or five times out of 100, significant results of the study occur because of random error or chance.

All research contains error. Typically, two types of error (Type I error: the rejection of a null hypothesis that should not be rejected, and Type II error: the acceptance of a null hypothesis that should be rejected) are relevant to hypothesis testing. There is always the possibility of making an error in rejecting or failing to reject a null hypothesis. It is not easy for researchers to balance these two error types, but one procedure, power analysis, helps researchers deal with the problem. Because power (the probability of rejecting the null hypothesis when it is true) indicates the probability that a statistical test of a null hypothesis will result in the conclusion that the phenomenon under study actually exists, if there is a difference, researchers are able to detect it.

Exercises

Let students look over the Journal of Broadcasting and Electronic Media since 1995 and have them collect hypotheses and research questions that researchers used. Discuss the criteria of a good hypothesis and research questions. Let students make three hypotheses in relation to their own research topics.

Practical Problems

Which are untestable hypotheses?

a)  Heavy viewers of Jerry Springer Show are very skeptical.

b)  American mothers would engage in more active mediation regarding sexually explicit Internet content, compared to Japanese mothers.

c)  Students with experience reporting for a university TV news program will perform better on a news reporting test than will students without this experience.

d)  Chinese hackers have more nation-oriented patriotism than American hackers.

e)  Elementary school students with no exposure to televised wrestling may act less aggressive behavior than those who watch this program.

f)  Einstein’s theory of relativity is more important than Newton’s principle of gravity.

Multiple Choice

1.  Which of the following statements is not related to exploratory research?

a)  The purpose of this research is to gather preliminary data

b)  This research is able to refine research questions

c)  This research try to find the causality between two variables

d)  This research often used by graduate students for theses and dissertations

2.  All of the following are benefits of hypothesis except that hypotheses:

a)  Provide direction for a study

b)  Eliminate trial-and-error research

c)  Rule out intervening and confounding variables

d)  Can establish cause and effect

3.  All of the following are criteria for useful hypotheses except that they should be:

a)  Compatible with current knowledge

b)  Be value-driven

c)  Succinct

d)  Testable

4.  Which of the following statements about Type I and Type II error is incorrect?

a)  Type I error is the rejection of a null hypothesis that should be accepted

b)  The probability of making a Type I error is equal to the established level of significance

c)  Type II error is controlled by the design of the research

d)  The researcher can control Type II error

5.  Statistical power is a function of three parameters. What does not belong to this group?

a)  Probability level

b)  Sample size

c)  Region of rejection

d)  Effects size

6.  In hypothesis testing, the researcher:

a)  Rejects or accepts the null hypothesis

b)  Rejects or accepts the substantive hypothesis

c)  May defer a decision to a later time