The t test for correlated groups requires that o the sampling distribution of raw scores is normally distributed o the sampling distribution of means is normally is normally distributed the population raw scores are normally distributed O Nis greater than 30
When we sketch a sampling distribution of means, we often assume it will be normal in its shape, especially with a large enough sample size used for sampling means, even if the population distribution of scores we drew samples from is not normal in its shape. What allows us to make this assumption?
Which of the following is true about the sampling distribution of means? Shape of the sampling distribution of means is always the same shape as the population distribution, no matter what the sample size is. Sampling distribution of the mean is always right skewed since means cannot be smaller than 0. Sampling distributions of means are always nearly normal. Sampling distributions of means get closer to normality as the sample size increases.
A sampling distribution for i would be obtained by finding ... O a. the means of lots of samples of the same size from the same population O b. the means of lots of samples of the same size from different populations O c. the means of lots of samples of varying sizes from the same population d. the mean of a single sample
Sampling Distributions Given a sampling distribution of means, how are the mean and standard deviation determined (calculated)? If an original sampling is not normal, how many must we sample to say it is approximately normal? Given a sampling distribution of proportions, how are the mean and standard deviation determined (calculated)?
R problem 1: The reason that the t distribution is important is that the sampling distribution of the standardized sample mean is different depending on whether we use the true population standard deviation or one estimated from sample data. This problem addresses this issue. 1. Generate 10,000 samples of size n- 4 from a normal distribution with mean 100 and standard deviation σ = 12, Find the 10,000 sample means and find the 10,000 sample standard deviations. What are the...
If the distribution of the population is bimodal, then the sampling distribution for the sample means for this population with sample size 50 will be unimodal. True False
The purpose of the questions is to hammer home that the distribution of sampling means for a large number of samples always makes a normal curve. 2) The second question concerns the following pair of sample mean distributions: Which distribution came from samples with a larger sample size, the one on the left or the one on the right a) b) Why is the sampling distribution on the right a narrower distribution?
The sampling distribution of means is: A list of all members of the population you are studying. Also called the standard error of the mean. A set of numbers representing all of the possible sample means on a variable you could draw from a given population and a given sample size. A list of all members of the sample that you draw. 1 points Question 2 The standard deviation of the sampling distribution of means is called the: Margin of...
QUESTION 1 We can create a distribution of sample means by selecting all possible random samples of the same size from the population. a. True b. False QUESTION 3 If you select a sample of size 100 from a population of raw scores and construct a distribution of sample means, what shape will the distribution of samples means have? a. left skewed b. right skewed c. approximately normal d. more information is needed about the shape of the population of...