Hypothesis Testing Flashcards
What is the purpose of hypothesis testing?
To make decisions about a population based on sample data.
What is the difference between point estimation and hypothesis testing?
Point estimation estimates a value for a parameter, while hypothesis testing evaluates claims about the parameter.
Why might a potato chip company overfill bags slightly?
To avoid underfilling due to variability and to satisfy customers.
What role does the sample mean play in hypothesis testing?
It provides an estimate used to test claims about the population mean.
What are the example hypotheses for the potato chip factory?
Null: mean weight ≤ 15 oz; Alternative: mean weight > 15 oz.
Why do we care about sample variability in hypothesis testing?
High variability can make results less reliable or significant.
Why can two people come to different conclusions with hypothesis testing?
Different random samples can lead to different sample means and decisions.
What is the source of errors in hypothesis testing?
Random variation in the samples, not mistakes by the analyst.
What is the goal when studying errors in hypothesis testing?
To understand and control the probability of making errors.
Can you always be certain from a sample whether to reject the null hypothesis?
No, randomness can cause different outcomes even with correct procedures.
What is hypothesis testing?
A statistical method to make decisions using data, typically comparing a sample statistic to a population parameter.
What is the general goal of hypothesis testing in data science?
To infer information about a population from a sample and make decisions based on statistical evidence.
Why is randomness important in hypothesis testing?
Because different random samples can lead to different results, and understanding this helps manage the likelihood of errors.
What are the possible errors in hypothesis testing?
Errors come from random variation in samples, not from mistakes by the tester.
Why might a company put more than the required average amount in a product?
To ensure compliance due to variability in weights and avoid consumer dissatisfaction or legal issues.
What is an example of a hypothesis in the potato chip factory story?
Null: average chip weight ≤ 15 ounces; Alternative: average chip weight > 15 ounces.
What does a sample mean of 15.7 ounces imply in the potato chip example?
It seems promising but may not be statistically significant depending on variability and sample randomness.
Why do we need to ‘control’ errors in hypothesis testing?
To make more reliable decisions and reduce the chance of incorrect conclusions due to sample variability.
What is the importance of sample size in hypothesis testing?
Larger samples provide more reliable estimates and reduce variability, leading to better decision-making.
Why might two different people come to different conclusions using hypothesis testing?
Because they may select different random samples, leading to different sample means and decisions.
