Statistics Ch 6

If a population has a mean of 40 and a standard deviation of 8, what would the z-score be for a sample of 16 people with a mean of 46? 3 2 4 6

3

If a test has a population mean of 70 and standard deviation of 6, then what is the z-score for a sample of n = 9 scores with a mean of 76? 1 6 2 3

3

The Central Limit Theorem states that the shape of a sampling distribution becomes closer to what shape as the number of sample means in the distribution increases? Skewed Bimodal Uniform Normal

Normal

Question 2 of 6.1 is important, but can't be put here. According to the Central Limit Theorem, the mean of the sampling distribution of means - \mu_{\overline{X}}μX‾ - will equal... - the mean of the original population divided the square root of n. - Cannot be predicted without additional information. - the mean of the original population. - the mean of the original population divided by n-1.

the mean of the original population.

If a distribution has a mean of 30 and a standard deviation of 3, then what is the z-score for a sample of 4 scores with a mean of 27? -2 1.5 2 -3

-2

If a population has a mean of 60 and a standard deviation of 15, what is the z-score for a sample of 9 people with an average of 55? -5 -1 -0.33 15

-1

One reason that researchers nearly always gather data from samples of participants instead of entire populations is because.. samples provide more accurate data than populations. samples have larger means than populations. it can be impractical or even impossible to study populations. population parameters are generally biased.

it can be impractical or even impossible to study populations.

One reason that researchers nearly always gather data from samples of participants instead of populations is because.. - data analysis is easier for samples than for populations. - populations always contain missing data. - it is easier to gather data from samples than populations. - any group with n < 1000 is a sample.

it is easier to gather data from samples than populations.

If a distribution of raw scores has a strong positive skew, then, given a sufficiently large n, the mean of the sampling distribution will be equal to the _____ of the raw score distribution. mean median \mu/\sqrt{n} mode

mean

The distribution of all possible sample variances - if n is sufficiently large (e.g., n > 30) - will be... positively skewed. leptokurtic. uniform. mesokurtic.

mesokurtic.

As the size of samples in a sampling distribution increases (i.e., as n get bigger), then that distribution becomes... more similar to the shape of the original population distribution. flatter. wider. narrower.

narrower.

As the size of samples (n) in a sampling distribution increases, the shape of that distribution becomes more... similar to the original population distribution. uniform. variable. normal.

normal.

The central limit theorem says that when all possible samples of a sufficient size are taken from a population and their means are charted, that distribution of means will be... - platykurtic. - uniformly distributed. - normally distributed. - standardized.

normally distributed.

Question 3 1 / 1 pts The distribution of all possible sample means (of a given size) is called... - the sampling distribution of means. - the distribution of samples. - the population of raw scores. - the distribution of means.

the sampling distribution of means.

The distribution of all possible samples of a given size (e.g., n = 54 or n = 117) are taken from a population and their means are charted, that distribution is known as... - a standard mean distribution. - the mean of the population. - the sample distribution. - the sampling distribution of means.

the sampling distribution of means.

The distribution of all possible sample variances (of a given sample size) is called... the variance differential. the sample variance. the sampling distribution of variances. the distribution of sampled variances

the sampling distribution of variances.

If a person were to create a sampling distribution for sample standard deviations, then the mean of that distribution would be equal to... - cannot be calculated without additional information. - the square root of the standard deviation of the original distribution. - the standard deviation of the original distribution. - the mean of the original distribution.

the standard deviation of the original distribution.

The standard error is... - a common mistake in coding responses. - the population mean divided by n-1. - the standard deviation of the sampling distribution. - the measure of sample bias.

the standard deviation of the sampling distribution.

According to the Central Limit Theorem, if a research takes sufficiently large samples (e.g., n > 30) from a bimodal distribution, then the resulting sampling distribution will be... uniform. bimodal. platykurtic. unimodal.

unimodal.

If a distribution has a mean of 100 and a standard deviation of 15, then what is the standard error for a sample of 225 scores? 1 125 15 cannot be calculated without additional information

1

If the population mean for a distribution is 150 and the standard deviation is 20, then what is the z-score for a sample of 100 people with an average score of 153? 0.15 1.5 50 3

1.5

What is the standard error of a distribution if \sigmaσ= 20 and n = 25? -5 0.80 5 4

4

The standard error of a sampling distribution is a function of two things: The population size and the sample variance. The sample size and the sample range. The degrees of freedom and the degree of normality. The population standard deviation and the sample size

The population standard deviation and the sample size

A sampling distribution can be calculated for... any sample statistic. any population parameter. sample means only. population means only.

any sample statistic.

If a distribution of raw scores has a strong negative skew, then, given a sufficiently large n, the sampling distribution of means for that distribution will... - have a strong negative skew. - have a strong positive skew. - be uniform. - be normal.

be normal.