IndietroIntroductory Statistics Test 2 — Step-by-Step Study Guidance
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Q1. A data set has mean 40. If you subtract 40 from every value and add up the results, you get:
Background
Topic: Properties of the Mean
This question tests your understanding of how the mean relates to the sum of deviations from the mean.
Key Terms and Formulas
Mean (): The average value of a data set.
Deviation: for each data value .
Property: The sum of deviations from the mean is always zero: .
Step-by-Step Guidance
Let the data set have values: with mean .
Subtract 40 from each value: for each .
Add up all these results: .
Recall that , so .
Try solving on your own before revealing the answer!
Final Answer: C. 0
.
This demonstrates the property that the sum of deviations from the mean is always zero.
Q2. Which pair of measures are both resistant to extreme values?
Background
Topic: Measures of Center and Spread
This question tests your knowledge of which statistics are resistant (not affected much by outliers).
Key Terms and Formulas
Resistant measure: A statistic that is not greatly influenced by extreme values (outliers).
Median: The middle value; resistant.
Interquartile Range (IQR): ; resistant.
Mean, standard deviation, range, and variance are not resistant.
Step-by-Step Guidance
Recall which measures are resistant: median and IQR are resistant; mean and standard deviation are not.
Review each answer choice to see which pair includes only resistant measures.
Eliminate choices that include mean, standard deviation, range, or variance.
Try solving on your own before revealing the answer!
Final Answer: B. median and IQR
Both the median and IQR are resistant to extreme values, making them good choices for describing skewed data.
Q3. Two populations are measured in the same units. The population with the larger standard deviation:
Background
Topic: Standard Deviation and Dispersion
This question tests your understanding of what standard deviation measures about a data set.
Key Terms and Formulas
Standard deviation ( or ): Measures the typical distance of data values from the mean.
Dispersion: The spread of data values.
Step-by-Step Guidance
Recall that a larger standard deviation means data are more spread out from the mean.
Review the answer choices for the one that describes greater spread or variability.
Eliminate choices that refer to the mean or median, which are not directly related to standard deviation.
Try solving on your own before revealing the answer!
Final Answer: A. has more dispersion
A larger standard deviation means the data are more spread out (more dispersed) around the mean.
Q4. According to the Empirical Rule, about what percentage of data in a bell-shaped distribution lie within 3 standard deviations of the mean?
Background
Topic: Empirical Rule (68-95-99.7 Rule)
This question tests your knowledge of the Empirical Rule for normal (bell-shaped) distributions.
Key Terms and Formulas
Empirical Rule: For bell-shaped distributions:
Within 1 SD: about 68%
Within 2 SD: about 95%
Within 3 SD: about 99.7%
Step-by-Step Guidance
Recall the Empirical Rule percentages for 1, 2, and 3 standard deviations from the mean.
Match the correct percentage to the range "within 3 standard deviations".
Eliminate answer choices that do not match the Empirical Rule values.
Try solving on your own before revealing the answer!
Final Answer: D. 99.7%
According to the Empirical Rule, about 99.7% of data in a bell-shaped distribution lie within 3 standard deviations of the mean.
Q5. An observation has a z-score of 2.3. This means the observation is:
Background
Topic: Z-scores and Standardized Values
This question tests your understanding of what a z-score represents in terms of standard deviations from the mean.
Key Terms and Formulas
Z-score: (for population) or (for sample)
Interpretation: The number of standard deviations a value is above or below the mean.
Step-by-Step Guidance
Recall that a positive z-score means the value is above the mean.
The magnitude of the z-score tells you how many standard deviations away from the mean the value is.
Review the answer choices for the one that matches this interpretation.
Try solving on your own before revealing the answer!
Final Answer: A. 2.3 standard deviations above the mean
A z-score of 2.3 means the observation is 2.3 standard deviations above the mean.
Q6. Two variables are positively associated when:
Background
Topic: Association and Correlation
This question tests your understanding of positive association between two variables.
Key Terms and Formulas
Positive association: As one variable increases, the other tends to increase as well.
Correlation coefficient (): Measures the strength and direction of a linear relationship.
Step-by-Step Guidance
Recall the definition of positive association.
Review each answer choice for the one that describes both variables increasing together.
Eliminate choices that describe negative association or non-linear relationships.
Try solving on your own before revealing the answer!
Final Answer: C. as one variable increases, the other tends to increase
Positive association means both variables increase together.
Q7. In a boxplot, the median is left of the center of the box and the right whisker is much longer than the left whisker. The distribution is:
Background
Topic: Boxplots and Skewness
This question tests your ability to interpret the shape of a distribution from a boxplot.
Key Terms and Formulas
Boxplot: Visual summary of the five-number summary.
Skewed right: Longer right whisker, median left of center.
Skewed left: Longer left whisker, median right of center.
Step-by-Step Guidance
Recall that the direction of skewness matches the longer whisker.
If the median is left of center and the right whisker is longer, the distribution is skewed right.
Eliminate choices that do not match this description.
Try solving on your own before revealing the answer!
Final Answer: B. skewed right
A longer right whisker and median left of center indicate right skewness.
Q8. A distribution's shape is unknown. Which tool can you still use to describe the percentage of data within k standard deviations of the mean?
Background
Topic: Chebyshev's Inequality vs. Empirical Rule
This question tests your understanding of which rule applies to all distributions, regardless of shape.
Key Terms and Formulas
Empirical Rule: Applies only to bell-shaped (normal) distributions.
Chebyshev's Inequality: Applies to any distribution, regardless of shape.
Chebyshev's formula: At least of data within standard deviations of the mean, for .
Step-by-Step Guidance
Recall that the Empirical Rule requires a bell-shaped distribution.
Chebyshev's Inequality works for any distribution shape.
Identify which answer choice refers to Chebyshev's Inequality.
Try solving on your own before revealing the answer!
Final Answer: D. Chebyshev's inequality
Chebyshev's Inequality can be used for any distribution, even if the shape is unknown.
Q9. Which pair of variables would most likely have a negative correlation?
Background
Topic: Correlation Direction
This question tests your ability to identify pairs of variables that move in opposite directions.
Key Terms and Formulas
Negative correlation: As one variable increases, the other decreases.
Examples: Temperature and heating bill (as temperature rises, heating bill falls).
Step-by-Step Guidance
Review each pair and consider whether an increase in one variable is associated with a decrease in the other.
Eliminate pairs that are positively correlated or unrelated.
Identify the pair where the relationship is most likely negative.
Try solving on your own before revealing the answer!
Final Answer: A. outside temperature and a home's heating bill
As outside temperature increases, heating bills typically decrease, showing a negative correlation.
Q10. Which value cannot be a linear correlation coefficient?
Background
Topic: Correlation Coefficient Range
This question tests your knowledge of the possible values for the correlation coefficient .
Key Terms and Formulas
Correlation coefficient (): Measures linear association; must be between -1 and 1.
Possible values: .
Step-by-Step Guidance
Recall the allowed range for .
Check each answer choice to see if it falls within to $1$.
Identify the value that is outside this range.
Try solving on your own before revealing the answer!
Final Answer: D. −1.3
The correlation coefficient cannot be less than -1 or greater than 1.
Q11. Which list is ordered from weakest to strongest linear association?
Background
Topic: Interpreting Correlation Coefficient Magnitude
This question tests your understanding of how the magnitude of relates to the strength of association, regardless of sign.
Key Terms and Formulas
Strength of association: Determined by (absolute value of ).
Weaker association: closer to 0; stronger: $|r|$ closer to 1.
Step-by-Step Guidance
Take the absolute value of each in the list.
Order the values from smallest (weakest) to largest $|r|$ (strongest).
Match the answer choice that follows this order.
Try solving on your own before revealing the answer!
Final Answer: C. −0.10, 0.35, 0.60, −0.90
This list goes from weakest () to strongest () association.
Q12. A scatter diagram shows points forming a clear U-shape, and r = 0.02. Which conclusion is correct?
Background
Topic: Linear vs. Nonlinear Relationships
This question tests your understanding of what the correlation coefficient measures and its limitations.
Key Terms and Formulas
Correlation coefficient (): Measures strength of linear relationship only.
Nonlinear relationship: may be near zero even if a strong nonlinear pattern exists.
Step-by-Step Guidance
Recall that only measures linear relationships.
A U-shape is a strong nonlinear pattern, but will be close to zero.
Identify the answer that recognizes a nonlinear relationship despite being near zero.
Try solving on your own before revealing the answer!
Final Answer: B. There is no linear relation, but there is a nonlinear relation.
A U-shape shows a strong nonlinear relationship, but only detects linear association.
Q13. For a sample of n = 6, r = −0.92 and the critical value is 0.811. What should you conclude?
Background
Topic: Testing Significance of Correlation
This question tests your ability to compare the correlation coefficient to a critical value to determine significance.
Key Terms and Formulas
Critical value: Threshold for significance; compare to the critical value.
If critical value, the correlation is significant.
Sign of indicates direction (negative or positive).
Step-by-Step Guidance
Calculate .
Compare to the critical value (0.811).
If is greater, a significant linear relation exists; the sign tells you the direction.
Try solving on your own before revealing the answer!
Final Answer: A. A negative linear relation exists.
Since , the correlation is significant and negative.
Q14. In a contingency table, a marginal distribution is:
Background
Topic: Contingency Tables and Marginal Distributions
This question tests your understanding of marginal vs. conditional distributions in two-way tables.
Key Terms and Formulas
Marginal distribution: Distribution of totals for one variable, ignoring the other variable.
Conditional distribution: Distribution of one variable for a fixed value of the other variable.
Step-by-Step Guidance
Recall that marginal distributions are found in the margins (totals) of the table.
Conditional distributions are for a specific value of the other variable.
Identify the answer that describes a frequency or relative frequency for a row or column variable alone.
Try solving on your own before revealing the answer!
Final Answer: C. a frequency or relative frequency distribution of either the row or the column variable
Marginal distributions summarize one variable, using the totals in the margins of the table.