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| 6714823009 | Response variable | Measures the outcome of a study, dependent variable, y | 0 | |
| 6714823010 | Explanatory variable | Attempts to explain observed outcomes, indepdent variable, x | 1 | |
| 6714823011 | Scatterplots | Show the relationship betweeen two quantitive variables (bivariate data). Each individual in a data set appears as a fixed point. All data points are plotted but not connected | 2 | |
| 6714823015 | Positive association | As x increases, y increases | 3 | |
| 6714823016 | Negative association | As x increases, y decreases | 4 | |
| 6714823018 | Correlation (r) | Measures strength and direction ( + or - ) | 5 | |
| 6714823019 | Words to describe strength | Strong (when r is close to 1 or -1), moderately strong/weak, weak (when r is close to 0) | 6 | |
| 6714823020 | Words to describe direction | Positive, negative | 7 | |
| 6714823021 | Correlation coefficient | r |  | 8 |
| 6714823022 | r is resistant or non-resistant to outliers? | Non-resistant | 9 | |
| 6714823023 | If r=1 | Perfect positive linear slope | 10 | |
| 6714823024 | If r=-1 | Perfect negative linear slope | 11 | |
| 6714823025 | What is the units of r? | r has no units | 12 | |
| 6714823026 | What is the range of r? | -1 < r < 1 | 13 | |
| 6714823028 | Residual | Observed value (y) - predicted value (y "hat") | 14 | |
| 6714823029 | Least squares regression line (LSRL) | The line that makes the sum of the sqaures of the vertical distances of the data points from the line as small as possible. The LSRL minimizes the total area in all of the squares. AKA "prediction line" | 15 | |
| 6714823030 | What point is always on the LSRL? | (x¯, y¯ ) | 16 | |
| 6714823031 | Equation of the LSRL |  | 17 | |
| 6714823032 | Defining x and y | Where x denotes _______ and y denotes predicted _______ | 18 | |
| 6714823033 | If residual is positive... | residual = (y) - (y "hat") The predicted y was less than the observed y Prediction was an underestimate | 19 | |
| 6714980634 | If residual is negative... | residual = (y) - (y "hat") The predicted y (y "hat") was greater than the observed y Prediction was an overestimate | 20 | |
| 6714823053 | If residual = 0 | y - yˆ= 0 y = yˆ Prediction was accurate | 21 | |
| 6714823034 | b1 | Slope of the LSRL | 22 | |
| 6715018757 | b0 | y-intercept of the LSRL, the predicted y when x=0 | 23 | |
| 6714823035 | Interpretation of the slope of the LSRL | For every one unit increase in ___(x)___ the predicted ___(y)___ increases/decreases on average by ___(b)___ units | 24 | |
| 6714823038 | Coefficient of determination | Is the proportion of the variation in the values of y that is explained by the LSRL | 25 | |
| 6714823039 | r² | Coefficient of determination | 26 | |
| 6714823041 | r² measures... | "how good the LSRL is at predicting y" | 27 | |
| 6714823045 | Interpretation of coefficient of determination | r² % of the variation in ___(y)___ is accounted for by the LSRL | 28 | |
| 6714823046 | r² > ? | 0 (therefore, always positive) | 29 | |
| 6714823047 | r is negative or positive? | It can be both | 30 | |
| 6714823048 | The sign of r matches the sign of... | b1 (slope of the LSRL) | 31 | |
| 6715078644 | Residual Plot | When asked if a linear model is an appropriate model for the data, you MUST examine the ... | 32 | |
| 6714823055 | Residual Plot characteristic: Curved patterns | The LSRL will not be the best fit -Not linear, so a line won't be the best choice | 33 | |
| 6714823054 | Residual Plot charcteristic: Idealized patterns | Random, uniform scatter of points above and below the LSRL residual | 34 | |
| 6714823056 | Residual Plot characteristic: Varying spread | As x increases, the prediction will be more accurate for some values and less accurate for others | 35 | |
| 6714823057 | Outlier | An observation that lies outside the overall pattern of the other observations. | 36 | |
| 6714823058 | Influential | An observation that if it is removed it would drastically change the result of some calculation (either r or r squared) | 37 | |
| 6714823059 | R-squared adjusted | NEVER USE | 38 | |
| 6714833301 | Axes | When making a graph (including a scatterplot), NEVER forget to LABEL your... | 39 | |
| 6714858125 | Form, direction, and strength (IN CONTEXT) | "Describing the scatterplot" means to discuss the... | 40 |
