IndietroEssential Formulas and Concepts in Elementary Statistics
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Describing, Exploring, and Comparing Data
Measures of Central Tendency
Measures of central tendency summarize a data set with a single value that represents the center of its distribution.
Mean (Arithmetic Average): The sum of all data values divided by the number of values.
Mean (Frequency Table): Used when data are presented with frequencies.
Midrange: The value halfway between the lowest and highest values in the data set.
Formulas:
Mean:
Mean (Frequency Table):
Midrange:
Measures of Variation
Measures of variation describe the spread or dispersion of data values.
Standard Deviation (s): Measures the average distance of data values from the mean.
Variance (s2): The square of the standard deviation.
Standard Deviation (Frequency Table): Used when data are grouped by frequency.
Formulas:
Standard Deviation:
Standard Deviation (Frequency Table):
Variance:
z-Score
The z-score indicates how many standard deviations a value is from the mean.
Formula:
Percentiles
Percentiles indicate the relative standing of a value within a data set.
Percentile of value x:
Converting from kth percentile to data value:
Probability
Basic Probability Rules
Probability quantifies the likelihood of events occurring.
Mutually Exclusive Events:
Not Mutually Exclusive:
Independent Events:
Dependent Events:
Rule of Complements:
Conditional Probability:
Counting Principles
Counting principles are used to determine the number of ways events can occur.
Permutations (no elements alike):
Permutations (with alike elements):
Combinations:
Discrete Probability Distributions
Mean and Standard Deviation
For a discrete random variable, the mean and standard deviation summarize the expected value and variability.
Mean:
Standard Deviation:
Binomial Probability Distribution
Key Properties and Formulas
The binomial distribution models the number of successes in a fixed number of independent trials with the same probability of success.
Probability:
Mean:
Variance:
Standard Deviation:
Standard Score:
Sampling Distributions
Sample Mean and Proportion
Sampling distributions describe the distribution of sample statistics over repeated sampling.
Mean of Sample Means:
Standard Error of the Mean:
Standard Score for Sample Mean:
Estimation and Confidence Intervals
Confidence Interval for Proportion
Interval:
Margin of Error:
Confidence Interval for Mean (σ known)
Interval:
Margin of Error:
Confidence Interval for Mean (σ unknown)
Interval:
Margin of Error:
Sample Size Determination
For Proportion (unknown p):
For Proportion (known and ):
For Mean:
Hypothesis Testing
Test Statistics
For Proportion:
For Mean (σ known):
For Mean (σ unknown):
Degrees of Freedom:
For Two Proportions: Additional info: Formula inferred for clarity.
Correlation and Regression
Equation of Regression Line
Regression Line:
Additional info: a = intercept, b = slope; formulas for a and b are not provided but are standard in statistics.
Goodness-of-Fit and Contingency Tables
Chi-Square Test Statistic
Test Statistic:
Expected Frequency:
Degrees of Freedom:
Summary Table of Key Formulas
Concept | Formula |
|---|---|
Mean | |
Standard Deviation | |
Variance | |
z-score | |
Percentile | |
Permutation | |
Combination | |
Binomial Probability | |
Confidence Interval (Proportion) | |
Confidence Interval (Mean, σ known) | |
Confidence Interval (Mean, σ unknown) | |
Sample Size (Proportion, unknown p) | |
Sample Size (Proportion, known ) | |
Sample Size (Mean) | |
Chi-Square Test |