Statistics - Differences Between Two Proportions

These flashcards capture essential vocabulary and concepts related to the differences between two proportions in statistical analysis.

Confidence Interval

A range of values used to estimate the true population parameter.

Proportion

The ratio of a part to the whole, often expressed as a fraction or percentage.

Sample Statistic

A numerical characteristic or measure obtained by using the data values from a sample.

Difference Score

The outcome calculated by subtracting one group's proportion from another's.

Margin of Error

The range of values above and below the sample statistic that likely contains the true population parameter.

Hypothesis Testing

A method used to determine if there is enough evidence to reject a null hypothesis.

Two Proportions

A comparison between two categorical variables to determine if there is a significant difference in their proportions.

Z Score

A statistical measurement that describes a value's relationship to the mean of a group of values.

Independence Condition

A requirement that two samples must not influence each other in statistical tests.

Sampling Condition

Criteria that must be met regarding sample size to ensure results are valid.

Categorical Variables

Variables that represent categories or groups and can be counted.

Null Hypothesis (H0)

The hypothesis that there is no effect or no difference; the baseline for testing.

Alternative Hypothesis (H1)

The hypothesis indicating the presence of an effect or a difference.

Two-Way Table

A data table that displays the frequency distribution of variables.

Proportion of Successes (p)

The ratio of successes to the total number of trials in a sample.

Statistical Software

Tools used to analyze data and perform statistical tests automatically.

Type I Error

Rejecting the null hypothesis when it is actually true.

Type II Error

Failing to reject the null hypothesis when it is actually false.

Survivorship Rate

The proportion of a population that survives over a specific period.

Statistical Significance

A statistical statement of how likely it is that an obtained result occurred by chance.

Random Sampling

Selecting a random group from a population to ensure every individual has an equal chance of being chosen.

n1 and n2

Denote the sample sizes of the two groups being compared.

Population Parameter

A measurable characteristic of a population, often estimated through sample statistics.

95% Confidence Level

A confidence level indicating that there is a 95% probability that the confidence interval contains the true population parameter.

Experimental Study

Research where the researcher manipulates one variable to determine its effect on another.

Observational Study

Research where the researcher observes outcomes without manipulation.

Point Estimate

A single value given as an estimate of a population parameter.

Statistical Power

The probability that a statistical test will correctly reject a false null hypothesis.

Effect Size

A measure of the strength of the relationship between two variables.

Confidence Level Adjustment

The process of changing the confidence level, which alters the width of the confidence interval.

Survival Rate Difference

The comparison of the survival rates of two groups, typically expressed as a percentage.

Outcome Measure

A variable used to assess the effectiveness of an intervention.

Proportion Variance

A measure of the degree to which proportions vary due to sampling.

Statistical Analysis

The process of collecting, analyzing, interpreting, presenting, and modeling data.