Statistics and Sampling Methods Quiz

<p>Uniform Distribution (A)</p> Signup and view all the answers

<p>4 (A)</p> Signup and view all the answers

<p>It divides the population into clusters, then samples entire clusters. (D)</p> Signup and view all the answers

<p>It is particularly useful for populations spread over large geographic areas. (C)</p> Signup and view all the answers

<p>It is less efficient and may need a larger sample size for precision. (D)</p> Signup and view all the answers

<p>The survey must be based on a probability sample. (C)</p> Signup and view all the answers

<p>They ensure representation across various subgroups of the population. (B)</p> Signup and view all the answers

<p>Nonresponse error (D)</p> Signup and view all the answers

<p>Questions that mislead or confuse respondents (C)</p> Signup and view all the answers

<p>It typically involves selecting every nth individual from a list. (C)</p> Signup and view all the answers

<p>Variability in sample means from sample to sample (D)</p> Signup and view all the answers

<p>21 (C)</p> Signup and view all the answers

<p>It decreases (D)</p> Signup and view all the answers

<p>1.58 (D)</p> Signup and view all the answers

<p>Mean = population mean, Standard deviation = population standard deviation (C)</p> Signup and view all the answers

<p>Sample mean (D)</p> Signup and view all the answers

<p>21 (C)</p> Signup and view all the answers

<p>$\sigma_X = \frac{\sigma}{\sqrt{n}}$ (D)</p> Signup and view all the answers

<p>2.236 (C)</p> Signup and view all the answers

<p>2.236 (B)</p> Signup and view all the answers

<p>Population standard deviation (C)</p> Signup and view all the answers

<p>Standard Error of the Mean remains unaffected (A)</p> Signup and view all the answers

<p>21 (B)</p> Signup and view all the answers

<p>$rac{ ext{Sum}(X_i - μ_X)^2}{N}$ (B)</p> Signup and view all the answers

<p>Sample mean, population mean, sample size, and population standard deviation (D)</p> Signup and view all the answers

<p>16 (B)</p> Signup and view all the answers

<p>It becomes almost normal regardless of the population shape. (D)</p> Signup and view all the answers

<p>It is equal to the population mean. (A)</p> Signup and view all the answers

<p>It becomes smaller as n increases. (C)</p> Signup and view all the answers

<p>When n is 30 or more. (D)</p> Signup and view all the answers

<p>Standard deviation decreases as sample size increases. (A)</p> Signup and view all the answers

<p>It approaches a normal distribution. (C)</p> Signup and view all the answers

<p>$\frac{\sigma}{n}$ (A)</p> Signup and view all the answers

<p>For sample sizes larger than a certain threshold, typically 30. (D)</p> Signup and view all the answers

<p>n &gt; 30 (A)</p> Signup and view all the answers

<p>Normal distributions (B)</p> Signup and view all the answers

<p>0.5 (C)</p> Signup and view all the answers

<p>8 (A)</p> Signup and view all the answers

<p>0.3108 (C)</p> Signup and view all the answers

<p>0.4 (B)</p> Signup and view all the answers

<p>It becomes approximately normal. (B)</p> Signup and view all the answers

<p>They can be skewed if sample size is small. (A)</p> Signup and view all the answers

Dividing the population into groups (clusters) that are representative of the whole population, then randomly selecting some of these clusters for sampling.

A type of sampling where each member of the population has an equal chance of being selected. This helps ensure the sample is representative of the whole population.

A sampling method where the population is divided into subgroups based on specific characteristics (e.g., age, gender), and then a sample is drawn proportionally from each subgroup.

A sampling method where every nth element in a list is selected. It's easy to implement but might introduce biases if the list has a pattern.

The error that occurs due to using a sample instead of the entire population. It's always present since we're not surveying everyone.

The error caused by the survey being unable to reach the target population. It's like trying to survey everyone but missing some groups.

This error occurs when people don't respond to the survey, leading to a biased sample. It's like getting a skewed view because some people refuse to answer.

The error caused by poorly designed survey questions or inaccurate responses. It's like asking unclear questions and getting misleading answers.

The tendency of the sampling distribution of the sample mean to approach a normal distribution as the sample size (n) gets larger, irrespective of the population's distribution.

The average of all possible sample means is equal to the population mean. It represents the central tendency of the distribution.

The standard deviation of the sampling distribution of the sample mean, calculated by dividing the population standard deviation by the square root of the sample size.

As the sample size gets larger, the sampling distribution of the sample mean becomes more like a normal distribution, regardless of the shape of the population distribution. This allows us to use the normal distribution to make inferences about the population mean.

The average of all possible sample means. It is always equal to the population mean.

The standard deviation of the sampling distribution of sample means. It measures how spread out the sample means are around the population mean.

A distribution that shows the probability of each possible sample mean that could be obtained from a population.

The distribution of individual values in a population.

The distribution of sample means that could be obtained from a population.

The standard deviation of the population.

The mean of the population.

The number of data points in a sample.

The standard deviation of the sampling distribution of the sample mean, also known as the standard error of the mean, is calculated by dividing the population standard deviation by the square root of the sample size.

The sample mean (x̄) is the average of the values in a sample. It's used to estimate the population mean (μ).

The distribution of all possible sample means from a population is called the sampling distribution of the mean.

If the population distribution itself follows a normal distribution, the sampling distribution of the mean will also always be normally distributed for any sample size.

The sampling distribution of the mean becomes approximately normal for larger sample sizes, even if the original population distribution is not normal. This holds true for most distributions.

For fairly symmetric distributions, the sampling distribution of the mean is nearly normal for sample sizes greater than 15.

The standard error of the mean (SEM) measures the variability of sample means. It tells us how much the sample means are likely to vary from the true population mean.

The standard error of the mean decreases as the sample size increases. This means that larger samples tend to have more accurate estimates of the population mean.

If the population is normally distributed, the sampling distribution of the mean (the distribution of all possible sample means) will also be normally distributed.

The mean of the sampling distribution of the mean is equal to the population mean (μ). This means that the sample means are centered around the true population mean.

The standard deviation of the sampling distribution of the mean (also known as the standard error of the mean) is equal to the population standard deviation (σ) divided by the square root of the sample size (n).

The Z-score for a sample mean is calculated by subtracting the population mean (μ) from the sample mean (X) and dividing by the standard error of the mean (σ/√n).

The Z-score tells us how many standard errors away from the population mean the sample mean is. It helps us determine the probability of observing a particular sample mean.

The sampling distribution of the mean is a theoretical distribution that describes the behavior of sample means across many repeated samples from a population.