Statistics and Descriptive Analysis

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

<p>To provide a summary of the data (D)</p> Signup and view all the answers

<p>Making predictions about future events (D)</p> Signup and view all the answers

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

<p>Standard deviation is expressed in the same units as the original data (B)</p> Signup and view all the answers

<p>1 (C)</p> Signup and view all the answers

<p>68% (D)</p> Signup and view all the answers

<p>z = (x - μ) / σ (C)</p> Signup and view all the answers

<p>1 (A)</p> Signup and view all the answers

<p>A larger standard deviation makes the distribution wider and flatter. (D)</p> Signup and view all the answers

<p>6 to 14 (C)</p> Signup and view all the answers

<p>To simplify calculations and compare probabilities for different normal distributions. (A)</p> Signup and view all the answers

<p>17.8 to 20.2 hours (A)</p> Signup and view all the answers

<p>The range of values within which we are 95% confident the population mean falls. (C)</p> Signup and view all the answers

<p>A point estimate does not provide a range of plausible values for the population parameter. (A)</p> Signup and view all the answers

<p>The null hypothesis always includes the equal sign (=). (C)</p> Signup and view all the answers

<p>To determine if there is enough evidence to reject the null hypothesis. (B)</p> Signup and view all the answers

<p>An increase in the price of gasoline will reduce the quantity of gasoline consumers demand. (A)</p> Signup and view all the answers

<p>To provide a reference point for comparing the observed data. (B)</p> Signup and view all the answers

<p>The opposite of the null hypothesis. (A)</p> Signup and view all the answers

<p>There is no relationship between the price of gasoline and the quantity of gasoline consumers demand. (A)</p> Signup and view all the answers

<p>μ ≤ 450 (C)</p> Signup and view all the answers

<p>The critical value for a 0.05 level of significance in a one-tailed test (B)</p> Signup and view all the answers

<p>There is insufficient evidence to reject the null hypothesis. (A)</p> Signup and view all the answers

<p>Reject the null hypothesis, as the test statistic is greater than the critical value. (B)</p> Signup and view all the answers

<p>The probability of rejecting the null hypothesis when it is true. (C)</p> Signup and view all the answers

<p>The population parameter is usually unknown. (C)</p> Signup and view all the answers

<p>μ ≠ 450 (B)</p> Signup and view all the answers

<p>0.05 (D)</p> Signup and view all the answers

<p>To specify the conditions for rejecting or not rejecting the null hypothesis. (A)</p> Signup and view all the answers

<p>0.25 (B)</p> Signup and view all the answers

<p>There is not enough evidence to reject the null hypothesis. (A)</p> Signup and view all the answers

<p>A test where the rejection region is on the right side of the sampling distribution. (D)</p> Signup and view all the answers

<p>The rejection region is in the right tail. (A)</p> Signup and view all the answers

<p>Calculate the standard error of the mean. (B)</p> Signup and view all the answers

<p>All of the above. (D)</p> Signup and view all the answers

<p>The range of values where the null hypothesis is rejected. (C)</p> Signup and view all the answers

<p>The mean of all possible sample means (C)</p> Signup and view all the answers

<p>The sampling distribution of the sample mean (A)</p> Signup and view all the answers

<p>By summing all hourly earnings and dividing by the number of employees (B)</p> Signup and view all the answers

<p>To determine the accuracy of using the sample mean to estimate the population mean (C)</p> Signup and view all the answers

<p>A single value calculated from a sample to estimate a population value (B)</p> Signup and view all the answers

<p>To capture all possible variations in the sample means (C)</p> Signup and view all the answers

<p>The range of values for which the mean is likely to be found (C)</p> Signup and view all the answers

<p>Sampling saves time and resources compared to studying the entire population (A)</p> Signup and view all the answers

Statistical methods used to summarize data and describe its main features.

Statistics that represent the center point of a dataset: mean, median, mode.

The average value of a dataset, calculated by dividing the sum of all data points by the number of points.

The middle value in a dataset when ordered, or the average of the two middle numbers if there’s an even count.

The most frequently occurring value in a dataset.

Statistics that describe the spread or dispersion of data points: range, variance, standard deviation.

The average of the squared differences from the mean, indicating how far the data points are from the mean.

The square root of variance, providing a measure of dispersion in the same units as the dataset.

The process of selecting items from a population to make inferences about that population.

The average of all values in a population, denoted by the Greek letter μ.

A probability distribution of all possible sample means of a given sample size.

The average of a sample, often used to estimate the population mean.

A single value derived from a sample to estimate a population characteristic.

The average of all sample means, indicating the population mean's estimation accuracy.

Selecting samples in such a way that previously selected items cannot be selected again.

All the unique combinations of items that can be drawn from a population based on sample size.

A normal distribution with a mean of 0 and a standard deviation of 1.

The number of standard deviations a data point is from the mean.

Predicts the distribution of values in a normal distribution: 68%, 95%, 99.7%.

About 68% of observations lie within one standard deviation of the mean.

About 95% of observations lie within two standard deviations of the mean.

About 99.7% of observations lie within three standard deviations of the mean.

A symmetrical, bell-shaped distribution where most values cluster around the mean.

The hypothesis stating no effect or no difference; not accepted when evidence suggests otherwise.

Failure to reject H0 does not mean H0 is true; it only indicates insufficient evidence against it.

The threshold for significance in hypothesis testing, indicating risk of rejecting H0 when true.

Common levels of significance: 0.05, 0.01, and 0.10, used based on research context.

A researcher chooses the alpha level before testing; affects outcome interpretation.

Values calculated to determine whether to reject the null hypothesis; include z, t, F, and χ2.

Criteria set to decide when to reject or not reject H0 based on test statistics.

The area in the statistical distribution where we reject the null hypothesis.

A point that separates rejection and non-rejection regions in hypothesis testing, specifically 1.645 for one-tailed tests at the 0.05 significance level.

The hypothesis that contradicts the null; it represents a new effect or difference, such as H1: μ > 450.

A statistical test that determines the direction of an effect (greater than or less than).

A test that checks for effects in both directions (e.g., H1: μ ≠ 450).

The probability of rejecting the null hypothesis when it is true; commonly set at 0.05.

A range of values that likely includes a population parameter.

Interval where we expect the population parameter to be found 95% of the time.

A procedure to test a hypothesis using data.

A structured method for testing hypotheses in statistical analysis.

The likelihood that a relationship or result is not due to random chance.