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9.1-9.3
by Chelsea Gray
# 9.1-9.3

## Parameter, Statistics, and
Statistical Inference

### Parameter: a number that is a
summary characteristic of a
population

### Statstic: AKA sample Statistic

### Estimate: AKA sample estimate

### Statistical Inference: The procedures used to
make conclusions about population
parameters on the basis of sample statistics

## Questions about Parameters

### Parameter 1: population proportion

### Parameter 2: Difference in two
population proportions

### Parameter 3: Population Mean

### Parameter 4: Population Mean
for paired differences

### Parameter 5: Difference in
Two Population Means

## Sampling Distributions

### Sampling Distribution: the probability distribution of a
sample statistic, describing how values of a sample statistic
vary across all possible random samples of a specific size
that can be taken from a population

### Standard Deviation of x: standard deviation
of the sampling distribution of the sample
mean

### Standard Deviation of p: standard deviation
of the sampling distribution of a sample
proportion

### Standard Error: estimated value
of the standard deviation of a
statistic

5.0 stars - 1 reviews
range from 0 to 5

Population Parameter: Makes it clear that the parameter is associated with a population, not a sample

Sample Statistic: a number computed from sample values taken from a larger population

Sample Estimate: when the statistic is used to estimate the unknown value of a population parameter

Confidence Interval: an interval of values that the researcher is pretty sure will cover the true, unknown value of the population parameter

Hypothesis/Significance Testing: uses sample data to try to reject a hypothesis about the population. Usually to reject the notion that chance can explain the sample results, Null Value: a value that would indicate that nothing interesting is happening, Statistical Significance: rejecting the idea that the observed results are possible ir the null value is correct

a number between 0 and 1 that represents the proportion with that certain trait

this is used to compare some feature of the two populations

the average variable for everyone in the population

the mean that would be obtained if we took the differences for the entire population of possible pairs, Paired differences: data formed by taking the differences in matched pairs

parameter of interest when comparing the mean for the same quantitative variable in two different populations or two population groups formed by a categorical variable