Unit 3 Flashcards
Interpreting Correlation Coefficient
a statistical index of the relationship between two things (from -1 to +1)
Association in a Two Way Table
Bivariate Data
Consists of two variables, an explanatory and a response variable.
Two Way Table
A table containing counts for two categorical variables. It has r rows and c columns.
Scatterplot
a graphed cluster of dots, each of which represents the values of two variables
Different Types of Association in a Scatterplot
Direction (Positive/Negative), Form (Linear), Strength (Strong, Moderate, Weak)
Correlation Co
Response Variable
A variable that measures an outcome
Explanatory Variable
a variable that we think explains or causes changes in the response variable
Interpret Least Squares Line (Line of Best Fit)
a line drawn in a scatter plot to fit most of the dots and shows the relationship between the two sets of data
Interpret a Residual Plot
a scatterplot of the residuals (results) against the explanatory variable (what is assumed)
Intercepts of a Line
The intercepts of a line are the points where the line crosses, the horizontal and vertical axes
Slope of a Line
y2-y1/x2-x1 , interprets the direction
Coefficient of Determination
a measure of the amount of variation in the dependent variable explained by the regression equation
Equation of a Fitted Line
Interpolation
Allows estimation of a datapoint within a dataset
Extrapolation
Allows estimation of a datapoint out of a dataset
Observed Association vs Causal Relationship
Correlation does not indicate causation
Non Causal Explanations for an Association
- Coincidence
- Confounding due to a common response from a separate variable
Time Series Plot
Obtained by plotting the time in which a variable is measured on the horizontal axis and the corresponding value of the variable on the vertical axis. Line segments are then drawn connecting the points.
Time Series Plot Trends
Trend (The increasing or decreasing value in the series) , Seasonality (The repeating short-term cycle in the series) and Irregular Fluctuations (Random drops and rises in data).
Smooth Time Series Data
Data can be smoothed by using a simple moving average
