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statistics test 1
| Question | Answer |
|---|---|
| parameter | number that describes a population |
| statistic | number that describes a sample |
| stratified random sampling | population divided into groups called a strata, then a random sample is drawn from each stratum |
| cluster sampling | items drawn from population in groups, useful with large groups |
| systematic sampling | items are ordered and every kth item is chose to be in a sample |
| voluntary response sampling is | never reliable bc of opinions |
| sample of convenience | not drawn by defined method |
| population | entire collection of people about which info is sought |
| simple sample | lottery |
| two qualitative groups | nominal and ordinal |
| randomized experiment | study in which investigators assign treatment to experimental studies at random |
| observational study | assignment of treatment to groups is made by investigator |
| cohort studies | various interests are associated with an outcome |
| case control studies | two samples drawn, 1 has disease and one doesnt |
| prospective cohort studies | subjects followed over time |
| cross sectional cohort studies | measurement taken at one point in time |
| retrospective cohort studies | subjects sampled after outcome occurs |
| qualitative vs quantitative | Qualitative research focuses on words, meanings, and human experiences to answer "why" or "how". Quantitative research focuses on numbers and statistics to answer "how many" or "how much" |
| ordinal vs nominal | Nominal names categories without any order. Ordinal puts categories into a rank.Key Differences Nominal: Items are labels or names. You cannot sort them from low to high.Ordinal: Items have a logical order. You can say one is higher or lower than another. |
| nominal examples | Eye color (blue, brown, green), gender (male, female), pet type (dog, cat, bird). |
| ordinal examples | Survey answers (poor, average, good), education level (high school, college, degree), race place (1st, 2nd, 3rd). |
| discrete vs continuous | discrete data or variables involve things you can count in whole numbers, while continuous data or variables involve things you can measure down to fractions and decimals. |
| ratio vs interval | interval data has a fake zero that does not mean "none". Ratio data has a real zero that means complete absence of the thing being measured. |
| interval ex | Temperature in Celsius or Fahrenheit, IQ Scores: A score of zero does not mean a person has zero intelligence.Calendar Years |
| ratio ex | Weight and Mass: Zero kg/lbs means there is no weight at all. Ten pounds is genuinely twice as heavy as five pounds.Height and Length: Zero inches or centimeters means no length exists.Time and Duration: Zero seconds means an event took no time at all. |
| a cluster sample is one which | population is divided into groups and a random sample is drawn |
| a sample is a | subset of a population containing individuals observed |
| IQR = | Q3- Q1 |
| standard deviation= | square root of variance |
| mode | the number or value that appears most frequently in a set of data. |
| median | the middle number in a set of data when the numbers are sorted in order from least to greatest. |
| mean | the average value of a set of numbers |
| sample variance | find mean, subtract the mean from each number, square it, add up squared numbers, divide by number of data in samples minus 1 |
| how to figure out what values are 1 sd from mean | + and - sd from mean |
| % | 1 sd= 68% 2sd= 95% 3sd=99.7% |
| outlier | any number greater than the upper outlier |
| finding percentile | count how many numbers are in data set, find location of given percentile, times .percentile of value thats in that spot, find the number of that value in the list |
| upper and lower outlier boundaries | lower= Q1-IQR upper= Q1+IQR |
| finding quartiles | plug data from smallest to largest, split data in half, find middle two numbers of first half, average them, do same thing for last half |
| SD below mean value= | mean - (SD)(SD) |
| frequency | number of items in particular order |
| mean group data | find midpoint of eacg class, multiply each midpoint by frequency, add up results of all, add frequencies, divide results/frequencies |
| z score formula | z= x-u/o x=test score u=mean o=sd |
| test score from z score | plug in mean, sd, z score into x= |
| relative frequency | proportion of items in a particular category |
Created by:
cwehner125