Descriptive statistics

Question 1

What is inferential statistics?

Answer 1

Inferential statistics is making predictions, generalizations, or inferences about a population based on a sample of data drawn from that population.

Question 2

Inferential statistics includes:

Answer 2

• Point estimation
• Interval estimation
• Hypothesis testing
• Prediction

Question 3

What is point estimation?

Answer 3

• Definition: Point estimation involves using sample data to calculate a single value (the “point estimate”) that serves as the best guess for a population parameter (like the mean or proportion).
• Example: If you want to estimate the average height of students in a university, you might take a sample of 30 students and calculate their average height (e.g., 170 cm). This average serves as your point estimate for the true average height of all students.

Question 4

What is interval estimation?

Answer 4

• Definition: Interval estimation provides a range of values (called a confidence interval) within which the population parameter is expected to fall. This accounts for uncertainty in the estimate.
• Example: Continuing with the height example, instead of just stating that the average height is 170 cm, you might say it is between 165 cm and 175 cm with 95% confidence. This means you are fairly certain that the true average height lies within that range.

Question 5

What is hypothesis testing?

Answer 5

• Definition: Hypothesis testing is a formal procedure used to test assumptions or claims (hypotheses) about a population parameter. It involves setting up a null hypothesis (H0) and an alternative hypothesis (H1) and using sample data to determine which hypothesis is supported.
• Null Hypothesis (H0): The hypothesis stating there is no effect or no difference.
• Alternative Hypothesis (H1): The hypothesis that there is an effect or a difference.