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HTH 320 Exam 2: Statistics Questions and Answers, Exams of Statistics

James Madison University (JMU)Statistics

A comprehensive set of questions and answers covering various statistical concepts, including regression analysis, survey design, hypothesis testing, and statistical significance. it's a valuable resource for students studying statistics, offering a detailed review of key topics and their applications. The questions delve into different statistical methods and their interpretations, making it ideal for exam preparation or self-assessment.

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2024/2025

Available from 05/05/2025

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HTH 320 EXAM 2 QUESTIONS WITH ACCURATE SOLUTIONS
1) Regression -- Answer ✔✔
• Tests for a correlation
• Produces a line of best fit
• Then produces a regression equation
• Produces an ANOVA used to determine if the prediction equation is
significant or y using x
2) With regression, the value you are predicting is the dependent variable and the value
you know is the _______________ variable. -- Answer ✔✔ Independent
3) The goal of ___________ is often to determine whether differences in your
independent variable can help explain the differences in your dependent variable --
Answer ✔✔ Regression
4) For ____________ to be useful, it must have a moderate to strong correlation &
must have a significant ANOVA -- Answer ✔✔ Regression
5) R is the correlation coefficient & indicates the correlation ________________
between the variables. -- Answer ✔✔ Strength
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HTH 320 EXAM 2 QUESTIONS WITH ACCURATE SOLUTIONS

  1. Regression -- Answer ✔✔
  • Tests for a correlation
  • Produces a line of best fit
  • Then produces a regression equation
  • Produces an ANOVA used to determine if the prediction equation is significant or y using x
  1. With regression, the value you are predicting is the dependent variable and the value you know is the _______________ variable. -- Answer ✔✔ Independent
  2. The goal of ___________ is often to determine whether differences in your independent variable can help explain the differences in your dependent variable -- Answer ✔✔ Regression
  3. For ____________ to be useful, it must have a moderate to strong correlation & must have a significant ANOVA -- Answer ✔✔ Regression
  4. R is the correlation coefficient & indicates the correlation ________________ between the variables. -- Answer ✔✔ Strength
  1. the proportion of variance explained by the independent variable in regards to the regression model -- Answer ✔✔ R^
  2. Regression analysis produces an _________, which indicates if the predictive power = significant -- Answer ✔✔ ANOVA
  3. Examples of Linear Regression Output -- Answer ✔✔
  • The Model Summary Table indicates the correlation (R).
  • The R2 value indicates the amount of total variation explained by the independent variable.
  1. The ANOVA Table is used to determine if the regression line that has been determined as the best fit is useful (statistically significant) when predicting the... -- Answer ✔✔ dependent variable
  2. The Coefficients Table provides the necessary values to construct a... -- Answer ✔✔ Regression equation
  3. Y = bX +a -- Answer ✔✔ Linear regression equation
  4. Predict new values for the dependent variable given more than one independent variable. -- Answer ✔✔ Multiple regression
  5. This test describes the probability of a person surviving to a certain point in time. Recorded as HR (Hazards Ratio) -- Answer ✔✔ Cox regression
  1. Chi Square or a rank based test such as the Mann-Whitney-Wilcoxon (MWW) test or a Kruskal-Wallis test, is the typical statistical protocol for what scale? -- Answer ✔✔ Likert
  2. Likert responses can be summed and the sums treated as... -- Answer ✔✔ Interval data
  3. The probability of falsely rejecting a null hypothesis (Type I error). -- Answer ✔✔ Alpha
  4. A single value from a data set -- Answer ✔✔ Case
  5. A qualitative variable associated with categories -- Answer ✔✔ Categorical variable
  6. Given a sample from a population, the CI indicates a range in which the population mean is believed to be found. Usually expressed as a 95% CI, indicating the lower and upper boundaries. -- Answer ✔✔ Confidence interval
  7. Statistical confusion caused by a variable(s) that is/are not controlled by the researcher. -- Answer ✔✔ Confoundment
  8. Variables that are on the interval or ratio level. -- Answer ✔✔ Continuous variable
  9. The group of subjects that are not subjected to any treatment. -- Answer ✔✔ Control group
  1. Variables usually obtained by counting. -- Answer ✔✔ Discrete
  2. A value derived from the number of subjects and the number of levels within the independent variables within a study. -- Answer ✔✔ Degrees of freedom
  3. A study where neither the participants nor the researchers know who is in the control and treatment groups. -- Answer ✔✔ Double blind
  4. The group of subjects that receive a treatment. -- Answer ✔✔ Experimental group
  5. A graph depicting the frequency of data point occurrences -- Answer ✔✔ Frequency distribution
  6. A measure of the shape (flatness or peakedness) of a frequency distribution. -- Answer ✔✔ Kurtosis
  7. Classification of non-numerical data. -- Answer ✔✔ Nominal scale
  8. A frequency distribution in which the data form a symmetrical bell shaped curve partitioned into standardized distributions -- Answer ✔✔ Normal distribution
  9. The hypothesis that states there is no statistical difference between the data sets. -- Answer ✔✔ Null hypothesis
  1. A variable associated with numerical values that have a numerical meaning. -- Answer ✔✔ Quantitative variable
  2. Quantitative variables respond to... -- Answer ✔✔ Typical measurement properties
  3. The data points contained in an area equal to one quarter of the entire data set. -- Answer ✔✔ Quartile
  4. An event or pattern in which all outcomes are equally likely. -- Answer ✔✔ Random
  5. A subset of the population. -- Answer ✔✔ Sample
  6. A numerical value summarizing the sample. -- Answer ✔✔ Sample statistic
  7. When the P-value is equal to or less than the alpha value. -- Answer ✔✔ Statistical significance
  8. The group of subjects exposed to the treatment. -- Answer ✔✔ Treatment group
  9. The Alpha level set by the researcher is halved and then applied to both tails of the normal distribution. -- Answer ✔✔ Two-tailed test
  1. Rejecting the null hypothesis when it should not be rejected. -- Answer ✔✔ Type I error
  2. Accepting the null hypothesis when it should be rejected. -- Answer ✔✔ Type II error
  3. False Positive error -- Answer ✔✔ Type I
  4. False Negative error -- Answer ✔✔ Type II
  5. Statistical tests that are designed to be used with data that are determined to be normally shaped and normally distributed. -- Answer ✔✔ Parametric tests
  6. Statistical tests that are distribution free; data do not have to conform to defined distribution characteristics. -- Answer ✔✔ Nonparametric tests
  7. T/F: In nonparametric tests, data has to conform to defined distribution characteristics -- Answer ✔✔ False
  8. A theorem that states that given a large enough sample, the shape of a distribution of samples from such a sampling distribution will approach a normal distribution. -- Answer ✔✔ Central limits theorem
  9. A probability distribution describing data that are limited to two outcomes -- Answer ✔✔ Binomial Distribution
  1. This value indicates the maximum threshold of probability of obtaining a particular set of data that the researcher is willing to except, given the null hypothesis is correct. -- Answer ✔✔ P value
  2. If a statistical test indicates that the probability of obtaining a particular data set was greater than the alpha level set by the researcher, the null hypothesis is ___________________ -- Answer ✔✔ Accepted
  3. T/F: We can conclude that we proved or disproved a hypothesis. -- Answer ✔✔ False
  4. If the statistical test indicates that the probability of obtaining a data set was less than the alpha level, it simply means that the data set would randomly occur _______ than 5 percent of the time. -- Answer ✔✔ Less
  5. Many statistical tests are designed to produce a ____________ value -- Answer ✔✔ Probability
  6. The _________ indicates the degree of extremeness associated with the data set, assuming the null hypothesis is true. -- Answer ✔✔ P value
  7. The p-value is compared to the _________ _________ set by the researcher. -- Answer ✔✔ Alpha level
  1. Researchers will reject the null hypothesis because the probability of obtaining the particular data fell _____________ (above or below) the .05 level -- Answer ✔✔ Below
  2. T/F: Although researchers reject the null hypothesis because the p-value was less than 0.5, this does not mean that a real difference was proven -- Answer ✔✔ True
  3. A significant p value only tells us that any differences between the groups being compared are not a consequence of... -- Answer ✔✔ Sampling error
  4. T/F: A significant p value does not tell us anything about the magnitude, importance or practicality of the differences -- Answer ✔✔ True
  5. Alpha levels and p-values are rooted in the ____________ ____________ theorem. -- Answer ✔✔ Central Limits
  6. The ____________ ____________ ____________ states that given large enough samples from a population, the distribution of sample means taken from this population will approach a normal distribution (bell curve or normal curve). -- Answer ✔✔ Central Limits Theorem
  7. The normal curve is sectioned by... -- Answer ✔✔ Standard deviations
  8. If we take a random samples from a population, the area under the bell curve associated with the sample will be representative of... -- Answer ✔✔ The probabilities associated with the likelihood of obtaining a particular sample mean.
  1. Given the means and standard deviations for each data set, if we find that a given amount of difference between data sets more than 5% of the time, the statistical analyses would produce a p-value (> or <) than 0.5? -- Answer ✔✔ >
  2. If a divergence of data sets occurs at or less than 5% of the time, researchers may postulate that this divergence may be due to -- Answer ✔✔ The unique characteristics of each data set
  3. With alpha set at .05 (p<.05), a p-value of .049 or less would indicate -- Answer ✔✔ Significance
  4. When a statistical test indicates significance at the .05 level, we can assume that the likelihood of difference between data sets occurring by chance is -- Answer ✔✔ Low
  5. T/F: The term "significant" means "a really important finding," or that a particularly large difference or relationship was found -- Answer ✔✔ False
  6. Problems with Null Hypothesis Significance Testing (according to Schmitz) -- Answer ✔✔ 1. Researchers want to know if the null hypothesis is true or false & NHST only tells us the probability of obtaining our data set given the null hypothesis is true
    1. All data sets are different
  8. Schmitz stated that in order to gain any useful info from NHST, researches must ensure that... -- Answer ✔✔ • Randomization has occurred
  • Samples are of a reasonable size
  • The selected alpha level takes into consideration the type of research / hypotheses being tested
  • P-values are accompanied by measures of effect size &/or CI
  1. The 95% confidence interval indicates -- Answer ✔✔ the observed range in which 95/100 sample means taken from this population (mean, median) would fall
  2. Outside of representing confidence interval, the abbreviation, CI, also symbolizes ______________ _________________, a biostatistical measure -- Answer ✔✔ Cumulative incidence
  3. _______________ _________________'s are good estimates of the range in which we may find the population parameter. -- Answer ✔✔ Cumulative incidence's
  4. The CI is always accompanied by a confidence level, usually at the ____% confidence level -- Answer ✔✔ 95%
  5. The 95% confidence level is similar to selecting .05 as an _____________ _____________ -- Answer ✔✔ Alpha level
  6. When we are testing the null hypothesis using a t-test, we can also use the ______ of the mean difference to determine if we have statistical significance -- Answer ✔✔ CI
  7. If the difference between the sample parameters lies outside of the 95% CI, we can conclude that we have __________________ at the .05 level because the CI indicates an estimate of a range of mean values that lie within the center 95% of the normal distribution -- Answer ✔✔ Significance
  1. The standardized effect size is calculated as: -- Answer ✔✔ [(Mean of Group A) - (Mean of Group B)] ÷ (Pooled Standard Deviation)
  2. Interpretation of effect size = 0.2 -- Answer ✔✔ Small effect
  3. Interpretation of effect size = 0.5 -- Answer ✔✔ Medium effect
  4. Interpretation of effect size = 0.8 -- Answer ✔✔ Large effect
  5. It would be extremely rare to find two samples that do not have any overlap & an effect size of ______ is an indication of 50% overlap. -- Answer ✔✔ 0.
  6. The _______________ ____________ of a study is an indication of the study design's capability of avoiding false negatives, or making a Type II error, when the researchers are trying to detect a specific effect size. -- Answer ✔✔ Statistical power
  7. Researchers are trying to create a healthy ____________ between the possibilities of Type I and Type II errors -- Answer ✔✔ Balance
  8. Researchers use the expected ____________, ____________ ____________, and the ____________ of the effect size to determine how many subjects are needed to reach a certain power. -- Answer ✔✔ Variance, alpha level, & magnitude
  1. T/F: Power is reported as often as it should be reported -- Answer ✔✔ False
  2. Power is not reported as often as it should be, which is in part due to researchers selecting sample sizes based on -- Answer ✔✔ Convenience
  3. Any study incorporating small sample sizes and failing to report the power of the study should be viewed with... -- Answer ✔✔ Caution
  4. Factors in which affect statistical power -- Answer ✔✔ • Alpha
  • Magnitude of the effect
  • Magnitude of the true difference
  • SD of the distributions
  • Sample size
  1. ___________ (more or less) power is needed if alpha is set below .05 -- Answer ✔✔ More
  2. If the difference between data sets is small, ___________ (more or less) power is required to detect such a difference. -- Answer ✔✔ More
  3. Everything else being equal, the more subjects = the___________ (more or less) power. -- Answer ✔✔ More
  4. To increase power from 0.80 to 0.90, multiply N by _________ -- Answer ✔✔
  1. Value for ______________ should be the standard deviation for the population -- Answer ✔✔ Sigma
  2. A single specification limit or pass/fail is a _____-sided test -- Answer ✔✔ One
  3. An upper and lower specification is a _____-sided test -- Answer ✔✔ Two
  4. The probability (p) of rejecting Ho when it is true & making a Type I error is called -- Answer ✔✔ Alpha / Level of significance
  5. What is the default 'Power of the Test' for the Power & Sample Size Calculator -- Answer ✔✔ 0.
  6. Why can statistics be perplexing? -- Answer ✔✔ • Statistics and probability are not intuitive.
  • We tend to jump to conclusions.
  • We tend to make overly strong conclusions from limited data.
  • We have incorrect intuitive feelings about probability.
  • We see patterns in random data.
  • We don't realize coincidences are common.
  1. A random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success is the same every time the experiment is conducted. -- Answer ✔✔ Bernoulli Trial
  2. T/F: Small samples can sometimes hide a significant pattern. -- Answer ✔✔ True
  1. T/F: All large differences are deemed statistically significant. -- Answer ✔✔ False
  2. The ________ the sample size the more likely we will have a significant finding, simply due to the size of the sample. -- Answer ✔✔ Larger
  3. Possible Statistical Outcomes -- Answer ✔✔ 1. There is no real difference and we find no significant difference.
  1. There is no real difference but we find a significant difference. (Type I error)
  2. There is a real difference but we fail to find a significant difference. (Type II Error)
  3. There is a real is a real difference and we find a significant difference.
  1. The _______________ _______________ does not allow us to determine, without any doubt, that there is or is not a real difference -- Answer ✔✔ Research method
  2. With the research method, we can only talk about _______________ associated with differences we find -- Answer ✔✔ Probabilities
  3. Researchers always run the risk of _______________ _______________ -- Answer ✔✔ False findings
  4. _______________ simply measure the degree of surprise associated with a finding -- Answer ✔✔ P-values