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### 58 Cards in this Set

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 statistics the art of collecting and organizing data as well as drawing inferences from the data descriptive statistics collecting organizing summarizing describing inferential statistics drawing conclusions from the data variable a characteristic that takes on different values for different people and places and things (must vary) quantitative variable a variable that can be measured in the usual sense qualitative variable a characteristic that cannot be measured in the usual sense - categorical population the largest collection of entities for which we have an interest at a particular time sample a subset of the population well representative sample when the characteristics of the sample match the characteristics of the population parameter numerical value based on the population statistic a numerical value based on the sample measurement the assignment of numbers to objects or events according to a set of rules four types of measurement nominal scale ordinal scale interval scale ratio scale nominal scale "naming observations" or classifying them into various mutually exclusive categories (ex: male/female) ordinal scale measurements can be ranked according to some criterion: low/average/high interval scale measurements can not only be ranked but the distance btwn the two is known - no true zero pt ratio scale measurements in which equality of ratios as well as equality of intervals is known - no true zero pt methods for obtaining data census sampling experimentation census get info from every element of the pop two types of samples nonprobability and probability examples of nonprobability samples sample of convenience haphazard selection judgment sampling expert sampling quota sampling sample of convenience samples already exist haphazard selection subjects casually met judgment sampling the researcher uses his/her own judgment in choosing the subjects expert sampling an "expert" picks the subjects quota sampling subjects are chosen so as to satisfy certain quotas (can also be probability sampling) probability samples when the sample is obtained by a chance process types of probability samples random samples stratified samples cluster samples systematic sampling random samples all samples of the same size have equal probability of being selected stratified samples population is divided into subpops (strata) and a random sample is obtained from each strata cluster samples randomly selecting some of the strata and obtaining a random sample from the chosen strata (subjects are naturally clustered together) systematic sampling choose a random starting pt from a list of subjs and then select every nth subject on the list selection bias when exclude a specific characteristic or segment of the population response bias when subjects respond incorrectly by lying or exaggerating or forgetting or not understanding the question (misleading question) nonresponse bias when the response rate is low two "types" of experiments observational study designed experiment observational study simply comparing two or more groups - only shows association designed experiment - control - randomization (div subjs into groups) - replication treatment group the group that receives the treatment control group group that does not receive the treatment blind study when the subjects don't know if they are receiving the treatment or placebo double-blind study neither the subjects nor the doctors know if subjects are in the treatment or control group problems w/ experiments placebo effect hawthorne effect rosenthall effect placebo effect when subjects improve because they believe they are receiving the treatment rosenthall effect when the researcher or experimenter unintentionally influences the outcome thru facial expressions or body lang or voice hawthorne effect when the outcome is affected because people change how they behave because they know they are being watched frequency distribution dot plot grouped freq distribution by age or grade histogram relative freq distribution percent measure of central tendency conveys a "typical" value of the data set ex: mean; median; mode properties of mean most commonly used may not be a value in the data set is not a resistance measure: mean will change when a value changes median value such that 50% of the data is smaller and 50% of the data is larger find location of median (n+1)/2 properties of median may not be a value in the data set is a resistance measure: median won't change when a value changes resistance measure a measure that is not affected by outliers measures of dispersion conveys info abt the amt of variability in the data: range variance standard deviation interquartile range variance measures the variability by comparing each data value to the mean -- not a resistance measure standard deviation measures the variability in original units -- not a resistance measure