Right-Tailed

Definition

Right-tailed refers to a probability distribution where the tail of the distribution extends more to the right side of the graph, indicating a skewed distribution with a longer right tail. This term is particularly relevant in the context of skewness and hypothesis testing involving population means.

5 Must Know Facts For Your Next Test

1. A right-tailed distribution has a longer right tail, indicating a positive skew, where the majority of the data is concentrated on the left side of the distribution with a few outliers on the right.
2. In the context of 2.6 Skewness and the Mean, Median, and Mode, a right-tailed distribution implies that the mean is greater than the median, which is greater than the mode.
3. For 10.1 Two Population Means with Unknown Standard Deviations, a right-tailed test is used when the alternative hypothesis suggests that the first population mean is greater than the second population mean.
4. Right-tailed tests are commonly used in hypothesis testing when the researcher is interested in determining if a parameter (such as a population mean) is greater than a specified value or greater than another parameter.
5. The direction of the tail (right or left) is determined by the alternative hypothesis, and it affects the critical value used in the test statistic calculation and the interpretation of the results.

Review Questions

• Explain how a right-tailed distribution is related to the relationship between the mean, median, and mode in the context of skewness.
  • In a right-tailed distribution, the mean is greater than the median, which is greater than the mode. This is because the longer right tail pulls the mean to the right, away from the mode, resulting in positive skewness. The median, being the middle value, is less affected by the skewness and lies between the mean and mode. This relationship between the measures of central tendency is a key characteristic of a right-tailed, positively skewed distribution.
• Describe the purpose and interpretation of a right-tailed hypothesis test in the context of comparing two population means with unknown standard deviations.
  • In the context of 10.1 Two Population Means with Unknown Standard Deviations, a right-tailed hypothesis test is used when the alternative hypothesis suggests that the first population mean is greater than the second population mean. The test statistic and critical value are calculated accordingly, and if the test statistic falls in the right-tailed critical region, the null hypothesis is rejected, and the conclusion is that the first population mean is significantly greater than the second population mean. The direction of the tail (right or left) is determined by the alternative hypothesis and affects the interpretation of the results.
• Analyze how the direction of the tail (right or left) in a hypothesis test impacts the critical value and the interpretation of the results.
  • The direction of the tail in a hypothesis test (right or left) is determined by the alternative hypothesis and has a significant impact on the critical value used in the test statistic calculation and the interpretation of the results. For a right-tailed test, the critical value is located in the right tail of the distribution, and the null hypothesis is rejected if the test statistic falls in the right-tailed critical region. Conversely, for a left-tailed test, the critical value is located in the left tail, and the null hypothesis is rejected if the test statistic falls in the left-tailed critical region. The direction of the tail directly affects the interpretation of the results, as it determines whether the evidence supports the claim that the parameter of interest is greater than, less than, or different from the hypothesized value.

Related terms

Skewness:

Skewness is a measure of the asymmetry of a probability distribution, indicating the degree and direction of the distribution's departure from symmetry.

Hypothesis Testing:

Hypothesis testing is a statistical method used to determine whether a claim or hypothesis about a population parameter is likely to be true or false.

Population Mean:

The population mean is the average value of a characteristic or variable within an entire population, as opposed to a sample mean, which is the average of a subset of the population.