Elementary Statistics
Midterm Exam
Course Introduction
Elementary Statistics introduces students to the fundamental concepts and methods of statistical analysis. Topics covered include data collection and organization, descriptive statistics, probability, distributions, estimation, hypothesis testing, correlation, and regression. Through real-world applications and hands-on exercises, students learn to interpret and communicate data effectively, develop critical thinking skills, and make informed decisions based on statistical reasoning. This course provides a solid foundation for further study in statistics and related fields.
Recommended Textbook
Statistics for People Who Think They Hate Statistics Excel 2010 Edition 3rd Edition by Neil J. Salkind
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532 Verified Questions
532 Flashcards
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Chapter 1: Statistics or Sadistics? Its Up to You
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Sample Questions
Q1) Which of the following formulas will add each of the scores together and divide the sum by 3?
A) x + y + z/3
B) x + y + (z)/3
C) (x + y + z)/3
D) x + y + z:3
Answer: C
Q2) Where will the results of the formula appear when you hit the Enter key?
A) in the selected cell
B) in the formula bar
C) in the toolpak
D) in the operator
Answer: A
Q3) When might a person use descriptive statistics?
Answer: Descriptive statistics are used to describe the characteristics of a data set.
Q4) What is a function?
Answer: A function is a predefined formula.
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Chapter 2: Means to an End: Computing and Understanding Averages
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Sample Questions
Q1) Determine the mode of the following set of scores: 10, 15, 12, 18, 19, 16, 12
Answer: The mode is 12
Q2) What are the measures of central tendency discussed in the textbook?
Answer: Mean, median, mode
Q3) To identify the point in a distribution at which 50% of scores fall above and 50% fall below a given score, which measure of central tendency would you report?
A) average
B) mean
C) mode
D) median
Answer: D
Q4) In a ranked list of 25 scores, the median is the score of
A) the 12th case
B) the 13th case
C) the average of the scores of the 12th and 13th cases
D) the average of all of the scores
Answer: B
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Chapter 3: Vive La Différence: Understanding Variability
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Sample Questions
Q1) What is the most frequently used measure of variability?
A) mean deviation
B) range
C) variance
D) standard deviation
Answer: D
Q2) Explain why the standard deviation is referred to as an unbiased estimate. Why are unbiased estimates important to researchers?
Answer: Because n - 1 is used in the denominator, we call the SD an unbiased estimate of the population's SD. By artificially inflating the SD, researchers are conservative in their estimate of the population SD.
Q3) What are the measures of variability discussed in the textbook?
Answer: Range, standard deviation, variance
Q4) What is the formula for computing both the exclusive and inclusive ranges?
Answer: Exclusive range: r = h - l; Inclusive range: r = h - l + 1
Q5) What is the formula for the standard deviation?
Answer: \(s = \sqrt { \frac { \sum ( X - \bar { X } ) ^ { 2 } } { n - 1 } }\)
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Chapter 4: A Picture Really Is Worth a Thousand Words
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Sample Questions
Q1) What is the term associated with a range of numbers that spans a set number of scores used when creating frequency distributions?
A) Histogram
B) Polygon
C) Class interval
D) Frequency count
Q2) If you wanted to examine the proportion of students in this class who are male compared to female, which of the following might you use?
A) Bar chart
B) Line graph
C) Pie chart
D) Histogram
Q3) What are the two types of skewness? Explain each.
Q4) What is another name for a cumulative frequency polygon?
A) Olive
B) Cumulative polygon
C) Ogive
D) Cumulative tally
Q5) What is the difference between skewness and kurtosis?
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Chapter 5: Ice Cream and Crime: Computing Correlation
Coefficients
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Sample Questions
Q1) If you wanted to compute the correlation between two ordinal-level variables, which type of correlation should you use?
A) Point biserial
B) Phi
C) Spearman rank
D) Pearson
Q2) If the coefficient of determination between two variables is .81, what is the coefficient of alienation?
A) .19
B) .34
C) .66
D) .90
Q3) If you wanted to compute the correlation between two nominal-level variables, which type of correlation should you use?
A) Point biserial
B) Phi
C) Spearman rank
D) Pearson
Q4) Write the formula for the Pearson product-moment correlation coefficient.
Page 7
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Chapter 6: Just the Truth: An Introduction to Understanding
Reliability and Validity
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Sample Questions
Q1) How does error affect reliability? Write the general equation for reliability that demonstrates this concept.
Q2) If I can say that my weekly statistics quiz fairly assesses the material covered, what source of validity evidence should I have collected?
A) Criterion validity
B) Content validity
C) Construct validity
D) Concurrent validity
Q3) If in the underlying continuum we are measuring assumed equal intervals, at what level of measurement is the associated variable being measured?
Q4) Which of the following is concerned with monitoring estimates of present performance and predictions of future performance?
A) Content validity
B) Criterion validity
C) Internal validity
D) Construct validity
Q5) What is the difference between reliability and validity?
Page 8
Q6) Name four types of reliability and what each type measures.
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Chapter 7: Hypotheticals and You: Testing Your Questions
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Sample Questions
Q1) What is the sampling error? What does a high sampling error indicate?
Q2) Which of the following symbols would be used in a nondirectional hypothesis?
A) \(<\)
B) \(=\)
C) \(>\)
D) \(\neq\)
Q3) Which of the following symbols represents the null hypothesis?
A) \(H _ { 1 }\)
B) \(\mu 1\)
C) \(\bar { X } 1\)
D) \(H _ { 0 }\)
Q4) Explain what is meant by the fishing trip approach to doing research.
Q5) Which of the following symbols represents the first research hypothesis?
A) \(H _ { 1 }\)
B) \(\mu 1\)
C) \(\bar { X } 1\)
D) \(H _ { 0 }\)
Q6) What are the different types of research hypotheses? What are they testing?
Q7) What are the basic criteria for judging the quality of hypotheses?
Q8) Explain the difference between the null hypothesis and a research hypothesis.
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Chapter 8: Are Your Curves Normal? Probability and Why It
Counts
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Sample Questions
Q1) How many standard deviations are included in a normal distribution with a mean of 100 and a standard deviation of 10?
Q2) Approximately what percent of scores fall between the mean and -1 to +1 standard deviations under the normal curve?
A) 34%
B) 14%
C) 68%
D) 95%
Q3) What characteristic of the normal curve deals with skewness?
A) Mean, median, and mode
B) Symmetry
C) Asymptotic
D) Probability
Q4) Which of the following is a characteristic of the normal curve?
A) Mean, median, and mode are different
B) Mean and median are the same but mode is different
C) Mean and mode are the same but median is different
D) Mean, median, and mode are the same
Page 10
Q5) What do standard scores allow researchers to do that raw scores cannot?
Q6) What are the characteristics associated with the normal curve?
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Chapter
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Sample Questions
Q1) Which of the following occurs when you accept the null hypothesis when it is really true?
A) Type I error
B) Correct decision
C) Type II error
D) Power
Q2) If the obtained value is less than the critical value, what should you do?
A) Reject the null hypothesis
B) Accept the null hypothesis
C) Reduce the p value
D) Decrease your sample
Q3) What does 1 - ? represent?
A) Alpha level
B) Type I error
C) Type II error
D) Power
Q4) What are the Greek letters associated with Type I and Type II error?
Q5) Under the normal curve, if the obtained value falls to the left of the critical value, under what percent of the normal curve did it fall?
Page 12
Q6) What is the definition for significance level?
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Chapter 10: Only the Lonely
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Sample Questions
Q1) A good reason to use a one sample Z-test is to know if the sample values are different from a given?
A) sample
B) value
C) collection
D) population
Q2) The observed sample mean?
A) Array
B) Mean score
C) Sigma
D) Mu
Q3) When you reject the null hypothesis when it is really true, then you have made a?
A) Incorrect decision
B) Correct decision
C) Type II error
D) Type I error
Q4) What can be said about data points and Z Tests?
Q5) When analyzing data types what type of chance should each individual have for being selected?
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Chapter 11: t(ea) for Two (Again): Tests Between the Means of Related Groups
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Sample Questions
Q1) What does the Excel function TTEST compute?
A) t value
B) Probability of the t value occurring
C) Critical t value
D) Obtained t value
Q2) What does t critical one-tail represent?
Q3) Examining one group of subjects under two different conditions would require what statistical technique?
A) Regression
B) t test for dependent samples
C) Analysis of variance
D) t test for independent samples
Q4) When using the Amazing Analysis ToolPak to compute t value for dependent samples, which test should you select?
Q5) What is the formula used to calculate degrees of freedom for a t test for dependent groups?
A) n - 1
B) n + n - 1
C) n - 1 + n
D) n + n
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Chapter 12: t(ea) for Two (Again): Tests Between the Means of Related Groups
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Sample Questions
Q1) To compute the test statistic or t value you must first approximate the sample size through calculating the?
A) Pooled variance
B) Standard deviation
C) Degrees of freedom
D) Mean score
Q2) If the obtained value is greater than the critical value, what should you do?
A) Reject the null hypothesis
B) Accept the null hypothesis
C) Set a higher p value
D) Increase your sample
Q3) To examine one group of subjects under two different conditions, which statistical technique should you select?
A) Regression
B) t test for dependent samples
C) Analysis of variance
D) t test for independent samples
Q4) What does P(T<=t) two-tail represent?
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Q5) Given the following, what should you conclude? t???? = 2.001 and tc??t?c?l = 1.94
Chapter 13: Two Groups Too Many? Try Analysis of Variance
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Q1) What is the first step in the computation of the F statistic?
A) Setting the level of risk
B) Selection of the appropriate test
C) Computing the obtained value
D) Stating the null and research hypotheses
Q2) When you compute the sum of the differences between each individual score and the group mean, you have calculated which of the following:
A) MS within
B) SS within
C) SS between
D) MS between
Q3) Which of the following would be an example of a design that examines the effects of gender and socioeconomic status (i.e., high, medium, and low) on a test of student achievement?
A) Simple ANOVA
B) One-way ANOVA
C) 2 × 3 ANOVA
D) 3 × 3 ANOVA
Q4) What is the formula for computing the F statistic?
Q5) What is the F value?
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Chapter 14: Two Too Many Factors: Factorial Analysis of Variance
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Sample Questions
Q1) When you want to examine the impact of more than one independent variable on the outcome variable, what type of ANOVA should be used?
A) Multivariate ANOVA
B) Factorial ANOVA
C) One-way ANOVA
D) Simple ANOVA
Q2) If your analysis notes that participants in a weight loss program differ in amount of weight lost based on their gender, what type of effect is this called?
A) Interaction effect
B) Factor effect
C) Level effect
D) Main effect
Q3) What is an analysis that examines more than one dependent variable or outcome known as?
A) Multivariate ANOVA
B) Complicated ANOVA
C) Two-way ANOVA
D) Univariate ANOVA
Q4) Create a 3 × 2 factorial design ANOVA.
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Chapter 15: Cousins or Just Good Friends? Testing
Relationships
Using the Correlation
Coefficient
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Sample Questions
Q1) In the formula for calculating degrees of freedom for a correlation coefficient, what does the n represent?
A) Sample size
B) Number of groups
C) Number of pairs
D) Population
Q2) Which of the following is an example of a null hypothesis for testing a correlation coefficient?
A) \(H _ { 1 : } \rho _ { x v } \neq 0\)
B) \(H _ { 1 : } : \rho _ { x w } = 0\)
C) \(H _ { 0 } : \rho _ { x v } = 0\)
D) \(H _ { 0 } : \rho _ { x w } \neq 0\)
Q3) What does a correlation coefficient represent?
Q4) What is another term for a positive correlation?
A) Indirect
B) Nondirectional
C) Direct
D) Unidirectional
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Q5) What two test statistics can be used to test the significance of a correlation coefficient?
Chapter 16: Predicting Wholl Win the Super Bowl: Using
Linear Regression
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Sample Questions
Q1) A positive trend line is associated with what type of slope?
A) Negative slope
B) Direct slope
C) Positive slope
D) Nondirectional slope
Q2) In order to use two predictor variables, what must be the case concerning the variables?
Q3) What must be done to categorical variables in order to use them in a regression analysis?
A) Nothing
B) Dummy coding
C) Problem coding
D) Categorical coding
Q4) What is the distance between each data point and the regression line called?
A) Error of estimate
B) Standard error of estimate
C) Standard deviation
D) Standardized error
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Q5) Write the equation for linear regression. What do the symbols represent?
Q6) What is the standard error of estimate? What does it allow us to examine?
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Chapter
Chi-Square and Some Other Nonparametric Tests
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Sample Questions
Q1) A one-sample chi-square is also known as which of these?
A) Goodness of fit test
B) Test of independence
C) Wilcoxon rank
D) Mann-Whitney
Q2) Which of the following nonparametric tests is used to determine if scores from a sample came from a specified population?
A) Mann-Whitney
B) Fisher's exact
C) Kolmogorov-Smirnov
D) Spearman rank
Q3) What is the level of risk associated with the null hypothesis called?
A) Type II error
B) Type III error
C) Power
D) Type I error
Q4) Explain when you would want to use a one-sample chi-square?
Q5) What is a parametric test?
Q6) What is the formula for calculating a one-sample chi-square?
Q7) Name two other nonparametric procedures, and explain when they would be used. Page 22
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Chapter 18: Some Other (Important) Statistical Procedures
You Should Know About
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Sample Questions
Q1) Which of the following is a path analysis technique used to present results in a graphical representation of the relationship between all the different factors under consideration?
A) data mining
B) structural equation modeling
C) covariance
D) ANOVA
Q2) Which regression analysis has more than one predictor variable?
A) multiple
B) covariance
C) repeated measures
D) factor
Q3) Of the following, which analysis can test relationships over time?
A) repeated measures
B) covariance
C) path analysis
D) ANOVA
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