Question | Answer |
complete collection of people, objects, scores, etc. to studied | population |
process of getting information from each element of the population | census |
any sub collection of data drawn from a population | sample |
any characteristic of the elements of the population | variable |
tells what values a variable has and how often those values occur | distribution |
value measuring some characteristic of a population | parameter |
value measuring some characteristic of a sample | statistic |
value that splits an ordered data set into 2 halves | median |
value that is far away from the rest of the data set | outlier |
average squared deviations from the elements to the mean | variance |
splits data set into 4 equal groups | quartile |
graph displaying the relationship between 2 variables | scatter plot |
value that measures the strength and direction of a linear relationship between 2 quantitative variables | correlation coefficient |
making predictions with values that are outside the range of x variables | extrapolation |
3 phases of statistics | gather data, analyze data, make inferences |
2 characteristics of a good sample | variety, size |
reasons to take a sample | saves time, saves money, destructive measures |
midrange formula | max + min / 2 |
variance of a sample symbol | s² |
standard deviation symbol | s |
variance formula | s²= n(Σx²)-(Σx)²/n(n-1) |
standard deviation equals the square root of the _____________ | variance |
slope symbol | b1, a (on calc) |
correlation coeffiecient of a sample symbol | r |
variance of a population symbol | σ² |
y intercept symbol | b0, b (on calc) |
regression equation | y(with a hat)= b1 * x + b0 |
standard deviation symbol (on calc) | Sx |
You can get variance by multipling standard deviance (Sx) by ____________ | itself |
variance answers are always ___________ | squared |
number of classes symbol | k |
population mean symbol | µ |
what does a 5 # summary consist of? | min, Q1, Q2 (median), Q3, max |
correlation coefficient formula | n * Σxy - Σx * Σy
r= ---------------------------------
sqr(n*Σx²-(Σx)²)*sqr(n*Σy²-(Σy)²) |
slope formula | n * Σxy - Σx * Σy
b1= ---------------------
n * Σx² - (Σx)² |
y intercept formula | b0 = (mean of y) - b1 * (mean of x) |