Inferential Statistics Flashcards

What is the primary goal of inferential statistics?

Answer: To make inferences about a population based on a sample

The primary goal of inferential statistics is to make generalizations or inferences about a larger population based on data collected from a smaller sample. This involves using statistical methods to draw conclusions, make predictions, and test hypotheses about population parameters. It extends findings beyond the observed data.

Which of the following is a point estimate?

Answer: Sample mean

A point estimate is a single value that is used to estimate an unknown population parameter. The sample mean is a common point estimate for the population mean, providing the best single guess for the true population average based on the observed sample data. Other examples include the sample proportion for the population proportion.

Which of the following statements best describes the confidence interval?

Answer: It is the range within which the population parameter lies, with a certain level of confidence.

A confidence interval provides a range of values, derived from sample data, that is likely to contain an unknown population parameter. It is associated with a specific confidence level, which represents the probability that the interval actually contains the true parameter. This gives a more informative estimate than a single point estimate.

What does the p-value represent in hypothesis testing?

Answer: The probability of obtaining a test statistic at least as extreme as the one observed, assuming the null hypothesis is true

In hypothesis testing, the p-value represents the probability of observing a test statistic as extreme as, or more extreme than, the one calculated from the sample data, assuming that the null hypothesis is true. A small p-value suggests that the observed data is unlikely under the null hypothesis, leading to its rejection. It helps determine the statistical significance of results.

Which of the following distributions is used when conducting a t-test?

Answer: t-distribution

The t-distribution, also known as Student's t-distribution, is specifically used when conducting a t-test. This distribution is appropriate when the sample size is small and the population standard deviation is unknown, requiring estimation from the sample data. It accounts for the increased uncertainty associated with smaller samples, providing a more accurate probability distribution than the normal distribution in these scenarios.