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Making Sense Of Statistics A Conceptual Overview 7th Edition Fred Pyrczak, Deborah M. Oh - Solutions
“Random sampling creates sampling errors.” This statement is true.false.
What is the most important characteristic of a good sample?Being free from bias.Being large.
“Using volunteers when sampling is presumed to create a bias.” This statement is true.false.
Parameters are based on a study of a sample.population.
Which type of statistics tells researchers how much confidence they can have when they generalize from samples to populations?Inferential.Descriptive.
“All populations are large.” This statement is true.false.
“It is necessary to use inferential statistics when conducting a census.” This statement is true.false.
If there is a perfect correlation, what is the value of the correlation coefficient?0.00.1.00.Some other value.
Which of the following is used to summarize data?Inferential statistics.Descriptive statistics.
“Measuring height using a tape measure is an example of the ratio scale of measurement.” This statement is true.false.
“The ordinal scale is a higher level of measurement than the interval scale.” This statement is true.false.
Which two scales of measurement tell us by how much participants differ from each other?Ordinal and nominal.Interval and ordinal.Ratio and interval.Nominal and interval.
If a teacher ranks students from low to high on their volleyball skills, he or she is measuring at what level?Ordinal.Interval.Ratio.Nominal.
If participants name their county of residence, the resulting data are at what level?Ordinal.Interval.Ratio.Nominal.
A survey is an example of an experimental study.a nonexperimental study.
Researchers try to change the participants in which type of study?Experimental.Descriptive.
Suppose students were treated with two types of rewards to see which one was more effective in promoting spelling achievement. Spelling achievement is the independent variable.dependent variable.
Treatments constitute which type of variable?Independent.Dependent.
Treatments are given in which type of study?Experimental.Nonexperimental.
What is a primary function of statistical analysis?Planning when observations will be made.Organizing and summarizing data.Identifying a population.
“Flawed research can be as misleading as everyday observations.” This statement is true.false.
If there are 800 teachers in a school district and 100 are selected for observation, the 100 are known as a population.sample.
“Everyday observation is an example of the empirical approach to knowledge.” This statement is true.false.
The empirical approach to knowledge is based on deduction.reliance on authority.observation.
Discuss a possible study topic that would require a simple linear regression, then develop it into a multiple regression.
If two independent variables show a high correlation in a multiple regression, what can you suspect in terms of their predictability of the dependent variable?
Discuss the difference between simple linear regression and multiple regression in terms of types of variables for each analysis.
What is the main distinction between correlation and regression in terms of their purpose?
Discuss how a regression analysis can develop from correlation coefficients.
Examine Example 1.Michelle has the fourth-highest attitude-toward-math score (a score of 12).However, she has an algebra grade near the bottom of the group (a grade of 1.5). What does this one case tell you about the relationship between attitude-toward-math and algebra grades? (Keep in mind that
Can multiple correlation coefficients be calculated for a combination of more than two predictors?
Suppose a researcher is examining the validity of a set of scores on an oral language test to predict a set of scores that first-graders will earn on a beginning reading test. Which correlational statistic should the researcher compute for this research problem (circle one)?A. r B. R
Suppose a researcher is examining the validity of a combination of the length of engagement and the number of hours in premarital counseling as predictors of subsequent marital satisfaction. Which correlational statistic should the researcher compute for this research problem (circle one)?A. r B. R
Suppose a researcher found a value of R of .40 for predicting the scores on variable Y from variables X and Z. Expressed as a percentage, what is the amount of variance in variable Y accounted for by the variance in the combination of variables X and Z?
Which of the following values of R represents the strongest relationship (circle one)?A. R = .45 B. R = .12 C. R = −.66
In the example in this chapter, which of the following is the best single predictor of algebra grades?(circle one) A. Basic math scores; B. Attitude-toward-math scores.
Inspection (without any computations) of the attitude-toward-math scores and the algebra grades in Example 1 above suggests that the correlation is (circle one) A. perfect; B. not perfect.
Inspection (without any computations) of the attitude-toward-math scores and the algebra grades in Example 1 above suggests that the correlation is (circle one) A. direct; B. inverse.
When the Pearson r = .40, is the percentage accounted for equal to 40%? Explain.
Do “large values” or “small values” of r shrink more dramatically when squared?
When r = .30, what percentage of the variance on one variable is not accounted for by the variance on the other?
When r = .30, what percentage of the variance on one variable is accounted for by the variance on the other?
When r = .50, what percentage of the variance on one variable is not accounted for by the variance on the other?
When r = .50, what percentage of the variance on one variable is accounted for by the variance on the other?
When r = .50, what is the value of the coefficient of determination?
What is the symbol for the coefficient of determination?
For a given value of r, how is the value of the coefficient of determination computed?
As noted in this topic, a small value of d might be associated with an important result. Name a specific problem that is currently confounding researchers and for which even a small value of d might indicate a result of great practical importance.
Should a test of statistical significance be conducted “before” or “after” d is computed and its value interpreted with labels?
Under what circumstance will a negative value of d be obtained?
According to Cohen (1992), what label should be attached to a value of d of 0.80?
What value of d is associated with the label “extremely large”?
If the value of d for the difference between two means equals 1.00, the experimental group’s mean is how many standard-deviation units higher than the control group’s mean?
Is the effect size for Question 1 “very large”?
For an experimental group, m = 50.00 and sd = 7.00. For the control group, m = 46.00 and sd = 8.00. For this experiment, what is the value of d?
Suppose a student made this statement: “Research shows that treatment with Alpha is significantly better than the Beta Treatment.” How would you respond to this student? Would you ask for additional information based on what you learned from this chapter? Explain.
According to this chapter, is determining practical significance a complex process?
Should practical significance be determined before statistical significance is determined?
In an experiment, what is the “ideal” finding regarding cost in relation to benefit?
Is it possible for an insignificant difference to have practical implications?
Can a small, significant difference sometimes be important?
Can a small difference be statistically significant?
Is the statement that “the difference is statistically significant” completely equivalent to saying “the difference is large”?
When should the null hypothesis be rejected (circle one)?A. When the probability (p) is low.B. When the probability (p) is high.
To what does the null hypothesis attribute differences?
If as a result of a Chi-square test, p is found to be less than .001, the odds that the null hypothesis is correct are less than 1 in ______?
Suppose you read that “χ2 = 2.824, df = 2, p > .05.” What decision should be made about the null hypothesis at the .05 level?
Suppose you read that “χ2 = 7.418, df = 1, p < .01.” Is this statistically significant at the .01 level?
Suppose you read that “χ2 = 4.111, df = 1, p < .05.” What decision should be made about the null hypothesis at the .05 level?
For examining relationships for nominal data, should a researcher use a “One-Way Chi-square test” or a“Two-Way Chi-square test”?
If you asked members of a random sample whether they planned to vote “yes” or “no” on a ballot proposition, would a “One-Way Chi-square test” or a “Two-Way Chi-square test” be appropriate?
If you asked members of a random sample (1) which of two types of skin cream they prefer and (2)whether they were satisfied with the condition of their skin, would a “One-Way Chi-square test” or a“two-way chi-square test” be appropriate?
If you asked members of a random sample which of two types of skin cream they prefer, and you wanted to compare the resulting frequencies with an inferential statistical test, would a Chi-square test be appropriate?
If you calculated the mean math test score for freshmen and the mean math test score for seniors and wanted to compare the two means for statistical significance, would a Chi-square test be appropriate?Explain.
Briefly describe a hypothetical study in which it would be appropriate to conduct a One Way ANOVA but not appropriate to conduct a t test.
Suppose that the participants were classified according to their grade levels and their country of birth in order to study differences among means for both grade level and country of birth. Does this call for a“One-Way ANOVA” or a “Two-Way ANOVA”?
Suppose participants were classified according to their grade level in order to test the differences among the means for the grade levels. Does this call for a “One-Way ANOVA” or a “Two-Way ANOVA”?
Suppose you saw this in the footnote to a One-Way ANOVA table: “p < .05.” Are the differences statistically significant?
Suppose you read this statement: “The difference between the means was statistically significant at the.01 level (F = 3.409, df = 14, 17).” Should you conclude that the null hypothesis was rejected?
Suppose you read this statement: “The difference between the means was not statistically significant at the .05 level (F = 2.293, df = 12, 18).” Should you conclude that the null hypothesis was rejected?
Which statistic in an ANOVA table is of greatest interest to the typical consumer of research?
If the difference between a pair of means is tested with ANOVA, will the probability level be different from that where the difference was tested with a t test?
“An ANOVA can be appropriately used to test only the difference between two means.” Is this statement“true” or “false”?
What is the name of the test that can be conducted with an ANOVA?
ANOVA stands for what three words?
Which type of author seldom explicitly mentions the null hypothesis?Authors of dissertations Authors of journal articles
you conclude that the null hypothesis has been rejected?
Suppose you read this statement: “For the difference between the means, t = 2.111 (df = 5, n.s.).” Should
For the statement in Question 4, should you conclude that the difference is statistically significant?
Describe in words the meaning of the statistical term “p > .05.”
Suppose you read this statement: “The null hypothesis was not rejected (t = –.926, df = 24, p > .05).”
Suppose you read this statement: “The null hypothesis was rejected (t = 2.810, df = 40, p < .01).” Should you conclude that the difference is statistically significant?
Suppose you read this statement: “The difference between the means is statistically significant at the .05 level (t = 2.333, df = 11).” Should you conclude that the null hypothesis has been rejected?
Which statistics should be reported before the results of a t test are reported?
Discuss a possible study topic that would require a One Sample t Test.
Assume that a One Sample t Test showed the following results: [t (49) = 4.21, p < .01]. Answer the following questions.What is the probability that the null hypothesis is true?What is the df of the study?What is the n of the study?What would you conclude?
How would you set up a one-tailed alternative hypothesis for the above example and what would you conclude if the null hypothesis was rejected?
For the above example, how would you set up a two-tailed alternative hypothesis and what would you conclude whether the null hypothesis was rejected?
One Sample t Test is used to test the difference between two sample means from one sample.SAT verbal scores are normally distributed with the population mean of 500.A local high school has instituted a new program to engage students in reading. A sample of 90 students from this high school is
One Sample t Test is used to test the difference between a sample mean and a population mean to determine statistical significance
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