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- 13-Jan
No category found.
- Slope.
- Residual.
- Y-intercept.
- Correlation coefficient.
- Describe the strength of a relationship.
- Predict the value of a dependent variable based on an independent variable.
- Compare population means.
- Test for independence.
- A perfect linear relationship.
- No linear relationship.
- A strong non-linear relationship.
- A causal relationship.
- A perfect positive linear relationship.
- No linear relationship.
- A perfect negative linear relationship.
- A weak negative linear relationship.
- A strong negative linear relationship.
- No linear relationship.
- A perfect positive linear relationship.
- A weak positive linear relationship.
- 0 to 1.
- -1 to 0.
- -1 to 1.
- -Infinity to +Infinity.
- Causal relationship between variables.
- Strength and direction of a linear relationship between two quantitative variables.
- Difference between means.
- Goodness of fit of a model.
- Two population means.
- Two population variances.
- Means of three or more populations.
- Proportions of three or more populations.
- Proportions of two populations.
- Variances of two populations.
- Means of two populations (especially with small samples or unknown population standard deviation).
- Relationships between two categorical variables.
- Confidence level.
- Critical value.
- Test statistic.
- P-value.
- Null hypothesis.
- Statistical hypothesis.
- Alternative hypothesis.
- Conservative hypothesis.
- Alternative hypothesis.
- Research hypothesis.
- Null hypothesis.
- Experimental hypothesis.
- Estimate population parameters.
- Determine the sample size.
- Make decisions about a population based on sample data.
- Visualize data.
- The probability that the parameter is exactly equal to the estimate.
- The proportion of times the confidence interval will contain the true population parameter if the process is repeated many times.
- The probability of making a Type I error.
- The precision of the estimate.
- Point estimate.
- Hypothesis.
- Confidence interval.
- Significance level.
- Interval estimate.
- Point estimate.
- Hypothesis.
- Confidence level.
- Testing a hypothesis.
- Calculating population parameters.
- Inferring population parameters from sample statistics.
- Collecting data.
