midterm 1 vocab Flashcards
what are the steps to the scientific method?
observation, hypothesis, measurements, results, conclusion (accept)
goal of stats
make strongest conclusion possible with limited information
2 main uses of stats
estimation (descriptive) and hypothesis testing (inferential)
population
total “universe” of all possible observations
sample
set of characteristics that make up subset of the population
variables
characteristics of individuals (age, color, etc.)
data
measurements of variables made on a sample (yellow/purple, male/female, etc.)
types of variables
numerical/quantitative or categorical/qualitative
types of numerical observations
continuous (range) or discrete (only select data values, counting)
types of qualitative data
nominal (no order) or ordinal (ordered)
what determines the type of stats test used?
type of variables and number of treatments
4 reasons why the sample can differ from the population
imprecision error (tools/tech), biological variability, mistakes (user error), non-representative data (bias)
bias
systemic differences between sample estimations and true population characteristics
random
every individual has an equal and independent chance of being selected for sample
purpose of random sampling
reduce bias and spread experimental error over all observations/treatments
types of bias
order, seasonal (only observing during a certain time of year), observer (Menke is a better evology info observer)
descriptive stats
describing a population based on sample data
what does descriptive stats measure?
central tendency (mean, median, mode) and spread (SD, variance, range)
what makes a good hypothesis?
identification of dependent and independent variables and is testable (can be run through tests) and falsifiable (can be proven wrong)
independent variable
predictor or explanatory, causes a response
dependent variable
response, the effect one is interested in
what does hypothesis testing do?
compare means while considering spread and sample size
calculates the probability of observing the results assuming the null hypothesis is true
what does the p-value represent?
probability
when can we reject the null hypothesis?
when the p value is less than 5%