Session 3 Statistical inference

A range of plausible values for a population parameter, calculated from a sample.

The probability that the true population parameter falls within the confidence interval.

The sample proportion, calculated as the number of successes divided by the sample size.

The number of observations in a sample.

A constant that determines the level of confidence in the interval.

The formula used to calculate a confidence interval for proportions.

The true proportion of the population that possesses a certain characteristic.

Adjusting the z-score value to change the desired level of confidence in the interval.

A statement that there is no difference between two populations, or that a population parameter is equal to a specific value.

A statement that contradicts the null hypothesis, suggesting a difference between populations or a deviation from a specified value.

A test where the alternative hypothesis suggests that the population parameter is simply not equal to the specified value in the null hypothesis.

A test where the alternative hypothesis suggests the population parameter is greater than the value specified in the null hypothesis.

A test where the alternative hypothesis suggests the population parameter is less than the value specified in the null hypothesis.

The process of starting by assuming the null hypothesis is true, gathering evidence (data) from a sample, and then using statistical methods to determine if the evidence supports the null hypothesis or the alternative hypothesis.

The process of calculating a probability based on the assumption that the null hypothesis is true, indicating how likely it is to observe the sample data if the null hypothesis is actually true.

A process used when the alternative hypothesis states that the population parameter is not equal to the specified value.

A unique identifier assigned to each individual in the General Social Survey (GSS) data set. This ID helps to distinguish one observation from another.

A categorical variable indicating the type of employer the survey respondent works for. It has two values: 1 for government and 2 for private employers.

A continuous variable representing the average number of hours worked per week by the survey respondent.

A continuous variable indicating the respondent's annual income from their primary job.

A continuous variable representing the number of years the respondent has been employed with their current employer.

A large-scale survey conducted every other year that gathers data on various social and personal characteristics of Americans. It is a valuable resource for social scientists and researchers.

Variables measured in the GSS data set that describe characteristics or attributes of the survey respondents.

The observations or individual responses collected in the GSS survey. Each observation represents a single person's data.

A statistical test used to compare the proportions of two independent samples. This test determines if there's a statistically significant difference in the proportions of a characteristic between two groups.

The hypothesis that there is no difference between the population proportions of two groups. It states that the proportions are equal.

The hypothesis that there is a difference between the population proportions of two groups. It states that the proportions are not equal.

The hypothesis that the population proportion of the first group is less than the population proportion of the second group.

The hypothesis that the population proportion of the first group is greater than the population proportion of the second group.

The hypothesis that the population proportion of the first group is different from the population proportion of the second group.

A value that represents the difference between two sample proportions. This difference is used in hypothesis testing to assess whether the difference between the sample proportions is statistically significant.

A statistical test used to compare the means of two independent groups. It helps determine if there's a significant difference between the average values of two populations.

The statement that there's no difference in means between the two groups. For example, assuming the average time spent at a job is the same for government and private sectors.

The statement that there is a difference in means between the two groups. For example, suggesting that government workers stay at their jobs for a different average time compared to private sector workers.

The difference in sample means between the two groups, calculated as the mean of group 1 minus the mean of group 2 (x̄1 - x̄2).

A statistical measure that indicates the amount of variability or spread of data points around the mean. It's used to determine if the difference in means is statistically significant.

The process of rejecting the null hypothesis when there is strong evidence against it. This means concluding that there is a significant difference between the means of the two groups.

The process of failing to reject the null hypothesis when there is not enough evidence to disprove it. This means concluding that there is not enough evidence to suggest a significant difference between the means.

A predetermined threshold used to decide whether to reject the null hypothesis. A p-value smaller than the significance level leads to rejecting the null hypothesis, suggesting a statistically significant finding.

A type of hypothesis test designed to evaluate whether there's a significant difference between two population proportions. It's used when comparing the proportions of successes in two different groups.

The estimated value of a population proportion based on a sample. It's calculated as the number of successes divided by the sample size.

A value that indicates how many standard deviations a sample proportion is away from the hypothesized population proportion. It's used in proportion tests.