BASIC MIDTERM REVIEW! Flashcards
3 possible test statistics
Binomial test (data to a specific hypothesized value)
Chi-squared goodness of fit test (ass no less than 1, no more than 20% less than 5)
Chi-squared contingency analysis (independence btwn 2 cat variables)
calc mean
average, calc like an average
median
middle measurement in a set of ordered data
standard deviation
symbolized by s = Positive square root of the variance!!! sqrt(s^2)
variance
*****. 1. Determine value of Y bar - MEAN OF SAMPLE/AVERAGE!!!!!
s^2 = sum from 1 to N of (sample value - average value)^2 / n - 1
n = sample size
standard error
the standard deviation of an estimate’s sampling distribution
odds
odds of success/odds of failure
if p = odds of success
odds = p/ (1-p)
odds ratio
odds of success in one group/odds of success in the other
BAE’s rule (Bayes theorum)
P(A|B) = P(B|A) * P(A) / P(B)
WHERE P(A|B) = probability of A given B
Graphs for single categorical variable
Bar graph, histogram, cumulative frequency distribution
Graphs for 2 variables: cat/cat
contingency table, grouped bar graph, mosaic plot
graphs for 2 variables: cat/num
multiple histograms, cumulative frequency distribution, line plot for cordial data only
graphs for 2 variables: num/num
scatter plot, line plot, map????
mode
most common value
range
max - min value
coefficient of variation
rep by CV = 100% s/Ybar = 100% standard deviation / average
why does coefficient of variation matter?
significancy of variation changes based on how large an organism/ something is
equation for (x / X) in binomial prob distribution equation
n! / [X! * (n - X)!]
0!
= 1
1!
= 1
mean of a binomial distribution
u = np where n = # of trials, p = probability of success
variance of binomial distribution
= np(1-p)
phat of a sample
proportion of successes in a sample (p hat) = X / n where X = number of successes, n = ind in a sample
mean of sample proportion
mean = p (the sample proporiton of successes)