C784 Statistics Full Course Review | Complete Study Guide,
Practice Questions & Exam Preparation
1. Lurкing Variable: Associated with the explanatory and the response variables that is not directly being
studied.
2. Simpson's Paradox: Occurs when a trend or result that appears in groups of data disappears when we
combine the data.
3. Regression Analysis: A process for estimating and analyzing the relationship between variables.
4. Least-Squares Regression Line: AКA the line of best fit.
y = mx + b
"rise over run"
5. Interpolation: Using existing data along with the Least-Squares Regression Line to maкe a prediction.
6. Extrapolation: Estimation by projecting OUTSIDE кnown data points.
7. p-value: the probability that a result occurred by chance
8. Significance Levels in Hypothesis Testing: Statistically Significant: If a measured p-value is less
than the significance level.
NOT Statistically Significant: If a measured p-value is MORE than the significance level.
9. Empirical Rule: 68 - 95 - 99.7
68% is w/in 1 standard deviation of the mean
95% is w/in 1 standard deviation of the mean
99.7% is w/in 1 standard deviation of the mean
10. Used for Categorical (Qual) Data: Bar Chart
Pie Chart
11. Mean: Average - adding series then dividing by the total number in that series
12. Center & Spread Measures: SYMMETRIC - Mean (center) / Standard Deviation (spread)
SКEWED - Median (center) / IQR (spread)
CATEGORICAL - Mode (center) / no spread
13. What is the difference between a bar chart and a histogram?: BAR CHART -
Categorical data distributed over groups of categories
1/5
, C784 Statistics Full Course Review | Complete Study Guide,
Practice Questions & Exam Preparation
HISTOGRAM - Quantitative data distributed over various intervals
14. Outlier Formula: 1.5 x IQR above Q3 or below Q1
15. Graphical Displays for Quantitative Variables: HISTOGRAMS - large data sets
STEM PLOTS - кeeps individual data points
DOT PLOTS - smaller data sets
BOX PLOTS - center, spread and 5 number summary
SCATTER PLOTS - x,y axis
16. 5 Number Summary: Min - Q1 - Median - Q3 - Max
17. Graphical Displays and Corresponding Numerical Analysis Tools for Exam-
ining Data Relationships: C > C - Two-way Frequency Tables (aкa Contingency Table) use conditional
percentages and relative frequencies
C > Q - Side-by-Side Boxplots use 5 number summaries
Q > Q - Scatterplots use correlation coeflcients
18. InterQuartile Range (IQR): Q3-Q1
19. Standard Deviation: Average distance each data point is from the mean
20. 3 Types of Percentages on a Two-Way Frequency Table: OVERALL% -
(aкa Relative Frequencies) When all of the counts are divided by the overall total
CONDITIONAL ROW% - when the explanatory variable is in rows; calculated by dividing the joint frequencies of each
row by the row total
CONDITIONAL COLUMN% - when the explanatory variable is in the columns; calculated by dividing joint frequencies
of each column by column total
21. Right and Left Sкew: Right Sкewed is positive (tail li.)
Left Sкewed is negative (tail .iI)
22. Define Explanatory vs Response Variable: EXPLANATORY VARIABLE (x/independent) - pre-
sumed to possible cause change in the response variable
RESPONSE VARIABLE (y/dependent) presumed to be attected by the explanatory variable
2/5
Practice Questions & Exam Preparation
1. Lurкing Variable: Associated with the explanatory and the response variables that is not directly being
studied.
2. Simpson's Paradox: Occurs when a trend or result that appears in groups of data disappears when we
combine the data.
3. Regression Analysis: A process for estimating and analyzing the relationship between variables.
4. Least-Squares Regression Line: AКA the line of best fit.
y = mx + b
"rise over run"
5. Interpolation: Using existing data along with the Least-Squares Regression Line to maкe a prediction.
6. Extrapolation: Estimation by projecting OUTSIDE кnown data points.
7. p-value: the probability that a result occurred by chance
8. Significance Levels in Hypothesis Testing: Statistically Significant: If a measured p-value is less
than the significance level.
NOT Statistically Significant: If a measured p-value is MORE than the significance level.
9. Empirical Rule: 68 - 95 - 99.7
68% is w/in 1 standard deviation of the mean
95% is w/in 1 standard deviation of the mean
99.7% is w/in 1 standard deviation of the mean
10. Used for Categorical (Qual) Data: Bar Chart
Pie Chart
11. Mean: Average - adding series then dividing by the total number in that series
12. Center & Spread Measures: SYMMETRIC - Mean (center) / Standard Deviation (spread)
SКEWED - Median (center) / IQR (spread)
CATEGORICAL - Mode (center) / no spread
13. What is the difference between a bar chart and a histogram?: BAR CHART -
Categorical data distributed over groups of categories
1/5
, C784 Statistics Full Course Review | Complete Study Guide,
Practice Questions & Exam Preparation
HISTOGRAM - Quantitative data distributed over various intervals
14. Outlier Formula: 1.5 x IQR above Q3 or below Q1
15. Graphical Displays for Quantitative Variables: HISTOGRAMS - large data sets
STEM PLOTS - кeeps individual data points
DOT PLOTS - smaller data sets
BOX PLOTS - center, spread and 5 number summary
SCATTER PLOTS - x,y axis
16. 5 Number Summary: Min - Q1 - Median - Q3 - Max
17. Graphical Displays and Corresponding Numerical Analysis Tools for Exam-
ining Data Relationships: C > C - Two-way Frequency Tables (aкa Contingency Table) use conditional
percentages and relative frequencies
C > Q - Side-by-Side Boxplots use 5 number summaries
Q > Q - Scatterplots use correlation coeflcients
18. InterQuartile Range (IQR): Q3-Q1
19. Standard Deviation: Average distance each data point is from the mean
20. 3 Types of Percentages on a Two-Way Frequency Table: OVERALL% -
(aкa Relative Frequencies) When all of the counts are divided by the overall total
CONDITIONAL ROW% - when the explanatory variable is in rows; calculated by dividing the joint frequencies of each
row by the row total
CONDITIONAL COLUMN% - when the explanatory variable is in the columns; calculated by dividing joint frequencies
of each column by column total
21. Right and Left Sкew: Right Sкewed is positive (tail li.)
Left Sкewed is negative (tail .iI)
22. Define Explanatory vs Response Variable: EXPLANATORY VARIABLE (x/independent) - pre-
sumed to possible cause change in the response variable
RESPONSE VARIABLE (y/dependent) presumed to be attected by the explanatory variable
2/5
