Inference for the Mean of a Single Population pt 1
• Cases = objects described by data set.
Can be customers, companies, subjects in a study, objects, etc
• label = special variable in some data sets to distinguish different cases
• variable = characteristic of a case
• categorical variable = each individual in a category
ex: male or female / ex: Yes or No
• Quantitative variable = numerical values that measure a characteristic of each case
Separate each observation into
– stem = all but the rightmost digit
– leaf = final digit
– Stems = as many digits as needed
– Leafs = contain only a single digit
Distribution of a variable = what values it takes / how often it takes these values
Stemplots and histograms display the distributions of quantitative variables
When examining a distribution, look for:
- shape, center, and spread
- for clear deviations from the overall shape Distributions shapes = symmetric or skewed.
The number of modes (major peaks) is another aspect of overall shape.
• less variable than individual observations.
• more “Normal” than individual observations.
The sample mean from a sample / xperiment is an estimate of the mean μ of the
MEAN / STANDARD DEVIATION OFASAMPLE MEAN
• is the mean of a SRS of size n from a population having mean μ and standard deviation σ.
The mean and standard deviation of are
SAMPLING DISTRIBUTION OFASAMPLE MEAN
• If a population