Introduction to Statistics

These flashcards cover key concepts related to statistics, including types of statistics, types of data, sampling methods, skewness, measures of center and variation, and the usage of Excel for statistics.

Descriptive Statistics

Statistical methods that summarize and describe the characteristics of a data set.

Inferential Statistics

Statistical methods that take a sample of data to make inferences or generalizations about a population.

Nominal Data

Categorical data that can be named or labeled but not quantified, like shirt colors.

Ordinal Data

Categorical data with a defined order, such as rating scales (e.g., Poor to Excellent).

Interval Data

Numerical data with a defined order and equal distances between points but no true zero, like temperature in Fahrenheit.

Ratio Data

Numerical data with a defined order, equal distances, and a true zero point, like the number of questions answered correctly.

Discrete Data

Countable data that can take only certain specific values, like the number of absences.

Continuous Data

Data that can take any value within a given range, such as time spent studying.

Simple Random Sampling

A sampling method where every member of the population has an equal chance of being selected.

Systematic Sampling

A sampling method where every kth member of the population is selected.

Convenience Sampling

A sampling method involving the selection of data that is easiest to access.

Stratified Random Sampling

A sampling method where the population is divided into groups, and members from each group are randomly selected.

Cluster Sampling

A sampling method where entire groups are selected at once as samples.

Left-Skewed Distribution

A distribution where the tail on the left side is longer than the right side, indicating that the mean is less than the median.

Right-Skewed Distribution

A distribution where the tail on the right side is longer than the left side, indicating that the mean is greater than the median.

Mean

The average value of a dataset, calculated as the sum of all values divided by the number of values.

Median

The middle value of a dataset when arranged in ascending order.

Variance

The measure of how far the values in a dataset are spread out from their mean, calculated as the average of the squared differences.

Standard Deviation

The square root of variance, representing the average distance of each data point from the mean.

Empirical Rule

The rule that states in a normal distribution, about 68% of data falls within one standard deviation of the mean.

Chebyshev’s Inequality

A principle that applies to all distributions and states that at least 1 - (1/k^2) of the data falls within k standard deviations from the mean.

Regression Formula

A formula used to predict the value of a dependent variable based on the value of one or more independent variables.

R^2 value

A statistical measure that represents the proportion of variance for a dependent variable that's explained by an independent variable.