Week 1 Day 1 - Mathematics

Use to organize, summarize, and present the values Draws NO consclusions “The data is the data”

Used to draw conclusions about data

variable with discrete or qualitative value male/female liking tofu 1-5 scale shirt (4 types) quarantine activity is qualitative, but is infinite, not discrete

variable that can measured along a continuum age temp height years as a nurse

categorical variable no intrinsic order - shirt, quarantine activity

categorical variables have order - tofu (1,2,3,4,5)

categorical variable only 2 values - m/f (order doesn’t matter)

continuous variable numeric value and is measured i.e. age, temp, height, years as a nurse

continuous variable like interval, but value of ‘0’ indicates there is nothing i.e. age, height, years as a nurse temp not ratio variable, nothing meaningful or valuable about my favorite temp being 70F and yours 75F

advantage: easy to calc disadvantage: affected by outliers ratio (height, age): yes interval (temp): yes ordinal (tofu): maybe, possible mathematically, but you shouldn’t nominal (shirt): no

advantage: outlier insensitive ratio (age, height): yes interval (temp): yes ordinal (tofu): yes nominal (shirt): no

ratio (age, height): yes interval (temp): yes ordinal (tofu): yes nominal (shirt): yes

mean, median, mode

describes the manner in which data are scattered around a specific value (such as the mean) range interquartile range standard deviation standard error of the mean percentile

highest value to lowest value ratio (age, heigh)t: yes interval (temp): yes ordinal (tofu): yes nominal (shirt): no

refers to the upper and lower boundary defining the middle percent of observations 75th percentile-25th percentile commonly used- 90th percentile-10th percentile ratio (age, height): yes interval (temp): yes ordinal (tofu): yes nominal (shirt): no

measure of variability how much people/subject differ from the the average (mean) ratio (age, height): yes interval (temp): yes ordinal (tofu): maybe (we can, but we shouldn’t) nominal (shirt): no

how well does the mean represent the sample error of the mean gets smaller as the sample gets bigger describes the amount of variability in the measurement of the population mean from several different samples ratio (age, height): yes interval (temp): yes ordinal (tofu): maybe (we can, but we shouldn’t) nominal (shirt): no

trying to reach conclusion that extend beyond the immediate data alone

There is no difference

simplest test for difference between 2 groups the greater the magnitude of “t”, the more likely the groups are different (statistically different)

bias chance confounders

caused by random variations in subjects and measurements larger sample size will reduce chance errors

systematic variation larger sample size WILL NOT help