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Marketing Final Exam
| Question | Answer |
|---|---|
| What does Sample Accuracy mean? | closeness of sample statistic to population value |
| What does Variability (s) mean? | how spread-out responses are. -how similar or dissimilar responses are to a given question |
| What does Population (N) mean? | Entire group of interest |
| What does Sample Size (n) mean? | Subset studied |
| What does Margin of Error (e) mean? | Range around estimate |
| What does Confidence Level (z) mean? | Probability interval contains true value |
| What does Representativeness mean? | How well sample reflects population |
| What does Descriptive Analysis mean? | Describes the typical respondent, describes how similar respondents are to the typical respondent (variability) |
| What is the statistical concept of Descriptive Analysis? | Typical: mean, median, mode Variability: frequency distribution, range, standard deviation |
| What does Inference Analysis mean? | Estimates population values, support or no support for hypothesized value. -Determines population parameters, tests hypotheses |
| What is the statistical concept of Inference Analysis? | Standard error, null hypothesis, Z value |
| What are the 2 types of measures in Descriptive Analysis? | -Central Tendency -Variability |
| What does Central Tendency mean? | Typical response, most frequent. Measures of Central Tendency (Mean, median, and mode) |
| How do you calculate/ find Mean, Median, and Mode? | Mean: Find the average! by adding all the numbers in the data set and dividing it by how many numbers there are Median: The middle number of the data set Mode: Look at the most frequent number of the data set |
| What does Variability mean? | How spread-out responses are diversity. Measures of Variability (Range, Standard Deviation, Frequency) |
| How do you calculate/find/know what Frequency Distribution, Range, and Standard Deviation are? | Frequency Distribution: Counts/percentages Range: Max-Min Standard Deviation (SD): Indicates the degree of variation or diversity in the values, linked to normal curve |
| What does Statistical Inference mean? | Using sample to estimate population |
| What are the two types of Inferences? | -Parameter Estimation (Confidence Interval) -Hypothesis Testing (Compare sample to hypothesis) |
| What is the difference between a "t Test" and a "z Test"? | t Test: statistical inference test to be used with small sample sizes (n<30) z Test: statistical inference test to be used when the sample size is 30 or greater (n>30) |
| What does an Independent Sample mean in the Difference Between Percentages with Two Groups? | This sample is representing two potentially different populations/ groups Example: Men vs Women |
| What does a Null Hypothesis mean? | No difference between groups. (Equals 0) |
| What does an Alternative Hypothesis (of Null Hypothesis) mean? | A real difference exists between the populations/groups |
| What does ANOVA do? or what is its purpose? | ANOVA is a screening tool — it tells you “Something’s different,” then you dig deeper. -Used for 3+ groups. -Tests whether at least one mean differs. -Green light procedure: Signals if differences exist, but not which ones. |
| What does Post HOC do? or what is its purpose being directly tied to ANOVA? | After ANOVA, use post hoc tests to find which groups differ -ANOVA is the alarm bell, post hoc tests are the detective work. |
| What does a Paired Sample test do? | Compare two means from the same respondents Example: satisfaction with product A vs. product B -Paired tests control for individual differences — you’re comparing within the same person, not across groups. |
| What does Associative Analysis mean? | Tests that determine if stable relationships exist between two variables. -Uncovers patterns of connection between two variables which is critical for understanding consumer behavior and designing strategies. |
| What is the difference between "Levels" and "Labels" | Levels: Interval/ratio (numeric scales) Example- X and Y variables Labels: Nominal/ordinal (categories) Example- Income and Brands |
| What is the difference between a "Linear" and "Curvilinear" relationship? | Linear: The two variables have a straight relationship. Linear relationships are predictable, and every unit change in X leads to a consistent change in Y Curvilinear: Smooth but not linear. The pattern describes the relationship. -A curve |
| True or False Not all relationships are straight lines; some effects accelerate or taper off | True |
| What is the formula for a linear relationship/straight line? | y= a+bx |
| What does Covariation mean? | How much two variables change together |
| True or False Correlation coefficient determines the range, sign, and magnitude (strength) of covariation | True -Correlation standardizes covariation so you can compare across variables |
| True or False A tight ellipse pattern is an example of a high correlated variable | True |
| What is Cross Tabulation? | A table showing frequency distribution of two categorical variables |
| How do you calculate "Raw percentages" in a Cross Tabulation table? | cell frequency/grand total |
| How do you calculate "Row percentages" in a Cross Tabulation table? | row cell frequency/row total |
| How do you calculate "Column percentages" in a Cross Tabulation table? | Column cell frequency/column total |
| What is a Chi-squared analysis? | Tests whether observed frequencies differ from expected frequencies |
| True or False In Chi-squared analysis, the null hypothesis is that the two variables are not related. We calculate expected frequencies to determine if we accept or reject the null hypothesis | True |
| True or False In Chi-squared analysis, observed frequencies are compared to expected frequencies | True |
| True or False If p>0.05 then we reject the null hypothesis | True |
| What does Degrees of Freedom mean? | How many values in your data are free to vary once the rules are set. Example: Imagine splitting $100 among 5 friends: You can freely decide amounts for 4 friends. The 5th friend’s amount is fixed (whatever is left). So you had 4 degrees of freedom. |
| What is the formula to calculate Degrees of Freedom? | (r-1)(c-1) |
| True or False The Chi-squared distribution is skewed to the right, and the shape of the distribution is dependent on degrees of freedom | True |
| True or False Statistical Inference = confidence that the observed pattern isn't random | True |
| What does Linear Regression analysis mean? | Regression is about prediction -Using one or more variables (independent) to estimate another (dependent) |
| What is the difference between Bivariate Regression and Multivariate Regression? | Bivariate Regression: Only two variables being analyzed, The impact of the SINGLE independent variable on a DEPENDENT variable Multivariate Regression: The impact of MULTIPLE independent variables on a DEPENDENT variable |
| What is the formula for Bivariate Regression? (Simple regression) | y= a + bx |
| What is the formula for Multivariate Regression? | Y = a + B1(X1) + B2(X2) + B3(X3)..... |
| True or False Overall regression tells us: -Which factors matter (significance) -How they matter (positive or negative) -How much they matter (size of coefficient) | True |
| In Regression Analysis, what does "Least squared criterion" mean? | Guarantees that the best straight-line slope and intercept will be calculated. (Finding the best line that describes the data) -Minimizes the squared errors between predicted and actual values |
| What's the only way of improving Regression Analysis? | Identifying an outlier |
| What does an Outlier mean? | A data point that is substantially outside the normal range of the data points being analyzed |
| True or False Outliers can distort the regression line | True |
| What does Multiple R (R squared) mean? | Also called the "Coefficient of determination" which is a measure of the strength of the overall linear relationship in multiple regression |
| True or False R squared ranges from 0 to 1 0= no explanatory power 1= perfect prediction | True |
| What does the Independence Assumption say/believe? | The independent variables MUST be statistically independent and UNCORRELATED with one another |
| True or False The presence of strong correlations among independent variables is called Multicollineanty | True |
| True or False Variance Inflation Factor (VIF) can be used to assess and eliminate multicollineanty | True |
| What does Variance Inflation Factor do? | Identifies what independent variables contribute to multicollineanty and should be removed -Any variable with VIF greater than 10 should be removed |
| True or False -Any variable with VIF greater than 10 shouldn't be removed | False |
| What does "Trimming" mean in regression? | You eliminate the nonsignificant independent variables, and then rerun the regression |
| True or False In the trimming process of regression, it has to iteratively remove nonsignificant betas until all remaining are meaningful | True |
Created by:
cydneywilli