Describing data using numerical summaries (such as mean, IQR, etc.) and graphical
summaries (histograms, bar charts, etc.).
Using sample information to make conclusions about a larger group of items/individu
Standard Deviation (of p-hat)
Approximately the average distance of the possible p-hat values (for repeated samples of
the same size n) from the true population proportion p
Standard Error (of p-hat)
Estimating, approximately, the average distance of the
Standard Deviation of the sample mean (s.d.(x-bar)
Measure of the accuracy of the process of using a sample mean to estimate the population mean.
This quantity (s.d./sq root of n) does NOT tell us exactly how far away a particular observed
sample mean val
A variable that both affects the response variable and also is related to the explanatory
Confounding variables might be measured and accounted for in the analysis, or they
could be un
study where treatments are randomly assigned to participants
treatment procedure that's assigned to a participant placebo
treatment that looks exactly alike the active (real) treatment (i.e. pill)
but contains no active (real) ingred
-symbol for: probability of event A happening
-between 0 and 1
-all (simple events) probabilities must equal 1
-in same sample space
-not same simple events
-^2 separate outcomes of one event
-P(A) + P(B) = 1
-LONG RUN FREQUENCY
-ex; probability of that a teen GAMBLES given that he is a BOY
Rule 1: event doesn't happen
- P(A c) = 1- P(A)
-P(A c) is the complement to P(A): so sum is equal to 1
Rule 2: either of two events happen
-general: P(A or B) = P(A) + P(B
Margin of error
number that you add and subtract from sample information
get: interval that's 95% certain ("truthful") about population
formula: 1/sq.root of sample
case study #4: who are those angry women?
about: only small portion of women who got quest
procedures and principles (rules)
make decisions when things are uncertain
case study #1: who are those speedy drivers?
about: females & males provide answers to fastest speed ever driven
moral: simple data summar
Places an individual or item into one of several groups or categories.
When a categorical variable has ordered categories, it is called an ordinal variable.
Visualized through a bar graph or pie chart.