To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.
- The data should include two categorical factors
For more information on factors, go to Factors and factor levels.
- If you have one categorical predictor and no continuous predictors, use One-Way ANOVA.
- If you have one continuous predictor, use Simple Regression.
- If you have more than one continuous predictor, use Multiple Regression.
- If you have one or more categorical predictors and continuous predictors, convert the categorical predictors to Make Indicator Variables before you perform multiple regression.
- The response variable should be continuous
- If the response variable is categorical, your model is less likely to meet the assumptions of the analysis, to accurately describe your data, or to make useful predictions. If you have a categorical response variable, use Cross Tabulation and Chi-Square.
- Collect data using best practices
To ensure that your results are valid, consider the following guidelines:
- Make sure the data represent the population of interest.
- Collect enough data to provide the necessary precision.
- Measure variables as accurately and precisely as possible.
- Record the data in the order it is collected.
- The model should provide a good fit to the data
If the model does not fit the data, then the results can be misleading. In the output, use residual plots, diagnostic statistics for unusual observations, and model summary statistics to determine how well the model fits the data.