Central Limit Theorem
Baye's Theorem
Rules For Probability
Sampling Distribution
Basic to the Basics
100

This theorem states that the sampling distribution of the sample mean tends toward normality as sample size increases.

What is the Central Limit Theorem?

100

This theorem updates the probability of a hypothesis based on new evidence

What is Bayes’ Theorem?

100

This condition holds when P(A and B) equals P(A) times P(B)

What is Independence? 

100

What is the output for For( I in 1:3)

1,2,3

100

This is the term for a subset of data drawn from a larger population.

What is a sample?
200

Empirical studies suggest this sample size is often sufficient for the sampling distribution to approximate normality.

What is 30?


200

In Bayes’ Theorem, this term represents the probability of a hypothesis before seeing the data.

What is the prior probability?

200

This is calculated by summing the products of each outcome and its probability

What is the expected value of a discrete random variable?

200

What is the purpose of Random Sampling?

To ensure that each object is equally likely to be in the sample population 

200

These two types of variables are commonly used in statistics—one is numerical, the other categorical.

What are quantitative and qualitative variables?

300

According to the CLT, even if the population is J-shaped or U-shaped, the sampling distribution of the mean will tend toward this shape.

What is a normal distribution?

300

 If E and F are independent, this simplifies the conditional probability P(EF).

 What is P(EF) = P(E)?

300

When the probability of an event is 0.5, the odds in favor of the event are this.

What is 1?

300

 The mean of the sampling distribution of the sample mean is equal to this value from the parent population.

What is the population mean?

300

This is the average of a set of numbers, calculated by summing all values and dividing by the count.

What is the mean?

400

 The sampling distribution of the mean will have this mean and this standard deviation, even if the population is non-normal.

What are mean = μ and standard deviation = σ/√n?

400

Bayes’ Theorem is especially useful when this type of probability is unknown and must be inferred from past data.

What is a conditional probability?

400

The number of ways to choose 4 genes from a set of 20 without regard to order.

What is 20 choose 4 or 20C4?

400

This is the formula for the standard deviation of the sampling distribution of the mean.

What is σ/√n, the standard error of the mean?

400

This value ranges from 0 to 1 and represents the likelihood of an event occurring.

What is probability?

500

This theorem allows us to compare the difference between two independent sample means, assuming both populations are normally distributed.

What is the theorem for sampling distribution of the difference between two independent means?

500

This type of representation can help visualize how prior and conditional probabilities interact in Bayes’ Theorem.

What is a graphical representation of Bayes’ Theorem?

500

This formula defines the probability of A given B.

What is P(A|B) = P(A and B) / P(B)?

500

When drawing infinite samples and plotting their means, this shape emerges even if the population distribution is rectangular.

What is a normal or bell-shaped curve?

500

How do you create a block in R?

What is ```{r} ```

M
e
n
u