Lecture 4 - Inferential Statistics Flashcards
What is inferential statistics?
Draws inferences about a larger population from a sample
What are the 2 methods of inferential statistics (IF)?
Estimation of parameters
Testing of statistical hypotheses
What is the relationship between descriptive stats (EDA) and Inferential stats (CDA)?
Need descriptive stats to assess the assumptions of the selected preliminary IF test and then decide which method of IF/IF test is the most suitable to be used
What is the objective of the estimation of parameters?
Determine population parameters which are unknown by estimating the population parameters based on sample statistics
What is sampling error? [4 ‘definitions’]
Amount of error in the estimate of a population parameter that is based on a sample statistic
does not mean a mistake
the value of a sample statistic will likely deviate from the parameter that is is estimating i.e. error in the estimate
variability of a statistic from sample to sample due to chance (random variability among samples)
sampling variation
What is sampling variation?
Extent to which a statistic varies in samples taken from the same population
How do we estimate sampling error? Give the theoretical and alternative method
Theoretical method, but true population value is unknown:
sampling error = population parameter - sample statistic
Alt. method: use sampling distribution of a statistic to measure the sampling error of that statistic
Describe the alternative method to estimating sampling error (2 parts)
Estimate population parameter from sample statistics
- sample statistic approximately = population parameter
- sampling error (SE) = standard deviation of sampling distribution = standard error of mean (SEM)
By CLT, if sample size is large enough
- normal sampling distribution
- mean of sampling distribution = population parmeter
- SE = SD of sampling distribution = (SD of sample statistics)/square root of sample size