Parameter
A numerical summary of a population. Its value is considered to be fixed and unchanging.
Population Parameter
Used to make it clear that the parameter is dealing with a population instead of a sample.
Statistic
A numerical summary of a sample. Its value may be different for different samples.
Sample Statistic
Synonym for Statistic.
Sample Estimate
Synonymous and reinforces the idea that a statistic often is used to estimate the corresponding population parameter.
Estimate
Synonym for Sample Estimate.
Statistical Inference
Information is used to make generalizations about a larger population. Sample statistics are used to make conclusions about population parameters.
Confidence Interval
An interval of values that the researcher is fairly sure will come true, unknown value of the population parameter.
Hypothesis Testing
Uses sample data to attempt to reject a hypothesis about the population.
Significance Testing
Same idea as Hypothesis Testing
Null Value
A value that would indicate that nothing of interest is happening.
Statistical Significance
Equivalent to rejecting the idea that the observed results are plausible if the null value is correct.
Population Proportion
A number between 0 & 1 representing the proportion with that trait.
Difference In Two Population Proportions
Used when we have two populations or have two population groups formed by a categorical variable & we want to compare some feature of the two populations.
Population Mean
With quantitative variables, one of the simplest summaries for the population is the average variable for everyone in the population.
Paired Differences
Data that are formed by taking the differences in matched pairs.
Population Mean For Paired Differences
The mean that we would get if we took differences for the entire population of possible pairs.
Independent Samples
The individuals in one sample are not coupled in any way with the individuals in the other sample.
Differences In Two Population Means
The parameter of interest is called this when we're interested in comparing the mean for the same quantitative variable in two different populations or two population groups formed by a categorical variable.
Sampling Distribution
The probability distribution of possible values of the statistic for repeated samples of the same size taken from the same population.
Standard Deviation of X-Bar
The standard deviation of the sampling distribution of a sample mean.
Standard Deviation of P-Hat
The standard deviation of the sampling distribution of a sample proportion. How far apart the sample proportion & the true population proportion are likely to be.
Standard Error
Describes the estimated standard deviation for a sampling distribution.
Sample Proportion
The proportion of trials resulting in success, or the proportion in the sample.
Normal Curve Approximation Rule for Sample Proportions
The sampling distribution for a sample proportion is approximately a normal distribution.
Sampling Distribution of P-Hat
The approximate normal distribution.
Standard Error of P-Hat
An estimated version of the Standard Deviation of P-Hat.
Sampling Distribution of P-Hat1 minus P-Hat2
The difference in population proportions.
Standard Deviation of P-Hat1 minus P-Hat2
The Standard Deviation when it comes to the sampling distribution of P-Hat1 minus P-Hat2.
Standard Error of P-Hat1 minus P-Hat2
When we don't know the population proportions, we use sample proportions instead.
Normal Curve Approximation Rule for Sample Means
If numerous random samples of the same size n are taken, the distribution of possible values of X-Bar is approximately normal.
Sampling Distribution of X-Bar
The approximate normal distribution of X-Bar.
Sampling Distribution of The Mean
Synonym for the Sampling Distribution of X-Bar.
Standard Deviation of The Sample Means
The parameter Sigma is a measure of the variability among the individual measurements within the population.
Standard Error Of The Mean
The standard error measures roughly how much, on average the sample mean X-Bar is in error as an estimate of the population mean Mu.
Dependent Samples
Data that are collected as matched pairs are sometimes called this because the two observations are not statistically independent of each other.
Sampling Distribution of D-Bar
The population mean of the differences.
Standard Deviation of D-Bar
(Sigma D) / (Square Root of N)
Standard Error of D-Bar
Used to estimate the standard deviation when Sigma D is not known.
Sampling Distribution of X-Bar1 minus X-Bar2
Difference in population means.
Standard Deviation of X-Bar1 minus X-Bar2
The standard deviation when it comes to the sampling distribution of X-Bar1 minus X-Bar2.
Standard Error of X-Bar1 minus X-Bar2
When we don't know the population standard deviations we use the sample standard deviation instead.
Standardized Statistic
Z = (Sample Statistic - Population Parameter) / S.D. (Sample Statistic)
Standardized Z-Statistic
Used to assess the difference between an observed sample proportion (P-Hat) & a possible value for the population proportion (P).
Student's T-Distribution
Distribution is called this when under certain conditions, it has a probability distribution.
Degrees Of Freedom (DF)
A parameter is called this when there's an association w/any t-distribution.
Standardized T-Statistic
t = (Sample Statistic - Population Parameter) / S.E. (Sample Statistic)
Law of Large Numbers
Guarantees that the sample mean X-Bar will eventually get "close" to the population mean Mu no matter how small a difference you use to define close.
Central Limit Theorem
States that if n is sufficiently large, the sample means of random samples from a population with mean Mu & finite standard deviation Sigma are approximately normally distributed with mean Mu & standard deviation (Sigma) / (Square Root of n)