## What is the mean value of this discrete random variable (discontinued)?

The mean of a discrete variable random variable X represents a weighted average among the possible values the variable could take. The mean of a discrete random variable is different from the sample mean of a collection of observations. It gives each observation equal weight. Instead, it weights each outcome xi based on its probability, pi.

**What is not a valid probability? **

1 Expert Answer Probabilities must be between 0 and 1 or 0% and 100% and cannot be negative. Therefore, 100% is valid for a probability, . 8 is valid for a probability, 75% is valid for a probability, while -. 2 is invalid for a probability.

**Is the following table a valid discrete probability distribution? **

Yes. All probabilities are between 1 and 0. The probabilities add up and make it one. The probabilities don’t add up to 1.

### What are the applications of probability under the normal curve?

These are: (i). To determine the proportion of cases within a given range or score. (ii) To find out the percentage of cases that exceed or fall below a reference point or score. (iii). To determine the limit of scores that include a certain percentage of cases.

**When sample size increases which of the following is correct? **

The relationship between margins of error and sample sizes is inverted. This means that if the sample size increases, then the sampling error decreases. This is because more information means that the results will be more accurate.

**What happens to the SEM as N is increased? **

The size of a statistical sampling affects its standard error. The standard error for a statistical sample is affected by the size (n) of its denominator. As a result, the standard error drops as n grows. You can see that more data means less variation and more precision in your results.

## What does increasing the sample size do quizlet?

A larger sample size increases the likelihood of finding a statistically significant effect. However, statistical significance is not necessarily a practical significance. 3. Sample size and variability: A larger sample size will produce a greater standard deviation increase power.

**How does mean change with sample size? **

The mean of the sample means is always approximately the same as the population mean u=3,500. Spread: Because larger samples have a wider spread, the standard deviation of the sample mean decreases with increasing sample sizes.

**What happens to the mean as sample size increases? **

Increasing Sample Size As sample sizes rise, sampling distributions become more normal. The population mean (u) is equal to the sampling distribution’s mean when there are infinite numbers of random samples.

### What is the central limit theorem try to state it in your own words?

The Central Limit Theorem is a statistical concept which states that the average distribution of random variables will assume a normal or near-normal distribution if there is enough sample size. The theorem says that the sampling distribution is the mean.