STAT chapt 3
Quiz yourself by thinking what should be in
each of the black spaces below before clicking
on it to display the answer.
Help!
|
|
||||
|---|---|---|---|---|---|
| cross–tabulation table | an arrangement of data in a two–way classification.
🗑
|
||||
| input variable | the variable we know or can control.
🗑
|
||||
| least squares criterion | requires finding the constants b0 (y–intercept) and b1 (slope) such that the sum of the squares of observed minus predicted values is as small as possible.
🗑
|
||||
| line of best fit | a line whose equation represents the smallest possible differences between the squares of observed minus predicted values on a line
🗑
|
||||
| linear correlation | the strength of a linear relationship between two variables, determined by the preciseness of shift in y as x increases.
🗑
|
||||
| linear regression | the straight line that best describes the relationship between two variables
🗑
|
||||
| lurking variable | a variable that is not included in a study but has an effect on the variables of the study and makes it appear that those variables are related.
🗑
|
||||
| negative correlation | a correlation in which an increase in x leads to a decrease in y.
🗑
|
||||
| ordered pairs | a mathematical expression (x, y) where x is the input variable written first, and y is the output variable written second.
🗑
|
||||
| output (dependent) variable | the predicted variable.
🗑
|
||||
| Pearson’s product moment formula | the formula that determines the coefficient of linear correlation (r).
🗑
|
||||
| positive correlation | a correlation in which an increase in x leads to an increase in y.
🗑
|
||||
| predicted value | the value of y calculated by modeling a particular value of x with a prediction equation.
🗑
|
||||
| prediction equation | an equation that models a mathematical relationship between x and y with an algebraic expression. Examples of prediction equations include linear (straight–line), quadratic, exponential, and logarithmic.
🗑
|
||||
| regression | the algebraic expression that describes the relationship between two variables
🗑
|
||||
| regression analysis | finds the equation of the line that best describes the relationship between the two variables under examination. That is, regression analysis describes the mathematical relationship between the two variables.
🗑
|
||||
| scatter diagram | a plot of all the ordered pairs of bivariate data on a coordinate axis system.
🗑
|
||||
| slope, b1 | the ratio of the rise over the run (horizontal distance) of a line. In the equation for a line of best fit, the slope is denoted b1.
🗑
|
Review the information in the table. When you are ready to quiz yourself you can hide individual columns or the entire table. Then you can click on the empty cells to reveal the answer. Try to recall what will be displayed before clicking the empty cell.
To hide a column, click on the column name.
To hide the entire table, click on the "Hide All" button.
You may also shuffle the rows of the table by clicking on the "Shuffle" button.
Or sort by any of the columns using the down arrow next to any column heading.
If you know all the data on any row, you can temporarily remove it by tapping the trash can to the right of the row.
To hide a column, click on the column name.
To hide the entire table, click on the "Hide All" button.
You may also shuffle the rows of the table by clicking on the "Shuffle" button.
Or sort by any of the columns using the down arrow next to any column heading.
If you know all the data on any row, you can temporarily remove it by tapping the trash can to the right of the row.
Embed Code - If you would like this activity on your web page, copy the script below and paste it into your web page.
Normal Size Small Size show me how
Normal Size Small Size show me how
Created by:
empire2311
Popular Math sets