Sampling Distributions Quizs

Describe sample distributions

• Shape, center, and variability.

• Mean, median, and mode.

• Range, interquartile range, and standard deviation.

• Skewness, kurtosis, and outliers.

SRS (Simple Random Sample)

• A method of sampling where each sample of the same size has an equal chance of being selected.

• A sampling method where samples are chosen based on specific characteristics.

• A technique that ensures every individual in a population is surveyed.

• A method that selects samples based on convenience and availability.

Statistic

• A number that describes some characteristic of a sample.

• A method for collecting data from a population.

• A graphical representation of data trends.

• A type of mathematical model used for predictions.

Sampling Distribution of the Sampling Proportion (p̂)

• Describes the distribution of values taken by the sample proportion p̂ in all possible samples of the same size from the same population.

• Refers to the average of all sample proportions from different populations.

• Indicates the likelihood of obtaining a specific sample size from a population.

• Represents the range of values for the population mean based on a single sample.

Unbiased Estimator

• If the mean of its sampling distribution is equal to the value of the parameter being estimated.

• If the estimator is always greater than the parameter being estimated.

• If the estimator is always less than the parameter being estimated.

• If the mean of its sampling distribution is less than the value of the parameter being estimated.

Sampling Distribution of the Sample Mean (x̄)

• Describes the distribution of values taken by the sample mean, x̄, in all possible samples of the same size from the same population.

• Represents the average of all sample means from different populations.

• Indicates the variability of individual data points in a single sample.

• Shows the relationship between the sample size and the population mean.

Parameter

• A number that describes some characteristic of a population.

• A variable that can take on different values.

• A fixed value that does not change.

• A statistical measure used to summarize data.

Central Limit Theorem

• It states that the mean of a sample is always equal to the population mean.

• It applies only to populations that are normally distributed.

• x-Bar is approximately normal if the sample size is large enough (n greater than or equal to thirty)

• It is used to determine the exact shape of any distribution.

Variability of p̂

• The standard deviation of the sampling distribution of p̂ can be calculated if the sample size is less than 10% of the population (10% condition).

• The standard deviation of the sampling distribution of p̂ is always equal to the population proportion.

• The standard deviation of the sampling distribution of p̂ can be calculated only if the sample size is greater than 30.

• The standard deviation of the sampling distribution of p̂ is irrelevant to the sample size.

10% Condition

• Used to describe variability in sampling distributions of p-hat and x-bar.

• Indicates that the sample size must be at least 30.

• Applies only to normally distributed populations.

• Is used to determine the margin of error in surveys.