stats first exam Flashcards
x < Q1-1.5(IQR) & x > Q3+ 1.5(IQR)
outlier formula
If there are outliers- use median to describe the data set (q1, q2, q3, mode more resistant)
If there aren’t outliers- use mean to describe the data set (mean, st less resistant)
mean median mode
three measures of central tendency
qualitative, labels, names
categorical variables
numbers you operate on
quantitative variables
univariate –> one var used
bi variate –> two var used
population- includes ALL the observations you are interested in
sample- includes 1 or more observations from the population, sample size can be more than the population because of replacement ex. 1000 size, everyone votes twice so sample expands
multiplying every value in a data set –> every value is affected and simply multiplied EXCEPT variance (which is found after calculating the deviation sum of squares)
st. d is multiplied by the square of the constant
{ (xi-u) squared
deviation sum of squares
x - u /o-
z score
Sx should NEVER be less than o- x because sample should always be bigger and its variance is divided by a lower number after finding deviation sum of squares
- quartiles
- percentiles
- z scores
3 measures of precision
use quartiles wit4h a row of numbers given, you can get 2 questions:
ex. what number is the 60th percentile
multiply 0.7 by the total number of data values in a set (round up if needed) and then count to find the number
OR ex. what percentile is 7 so you would count the number place 7 is in in the row and divide it by the total number of numbers and multiply by 100
- tells you how many st. d a data point is away from the mean!!!
- if z score = 0, the point is the mean
if z score = -3, the point is -3 st. ds below the mean
if z score = 5.7, the point is 5.7 st ds above the mean
z scores
after many many games we expect the team to score 30 points per game (their average!!)
interpreting mean
after many many games, each (!) of the bball games typically (!) result in them scoring 3 points AWAY FROM THEIR MEAN/AVERAGE of 30 points
interpreting st. d
In statistics, the capital letter “N” is used to represent the total number of observations or the size of the population (i.e.) N is the total number of cases in all groups whereas the small letter “n” represents the sample size.
