CNSL 503 Statistics Portage Exam 3 2025

Parameter - -a numerical value that describes a population Example of parameter - -population mean Statistic - -a value that describes a sample; used to estimate population parameter Example of a statistics - -sample mean In order to make correct inferences about the population, the sample must... - -reflect the population Representative sample - -consist of members that possess the same characteristics as those of the population Biased sample - -a sample that is not representative of the population 5 types of sampling techniques - -simple random sampling, systematic sampling, stratified sampling, cluster sampling, and convenience sampling Simple random sampling - -each member of the population has an equal chance of being selected for the sample Example of simple random sampling - -everyone in the population of interest rolls a die, everyone rolling a 6 gets selected In simple random sampling, the probability that each member is selected is ____ of one another. - -independent Simple random sampling is ideal for ____ populations. - -small Systemic sampling - -random sampling with a system in which a starting point is random and each subsequent member is selected based on a fixed interval Example of systemic sampling - -shoppers at a store, start with second person entering and survey every 5 shoppers In systemic sampling, the probability that each member is selected is ____of one another. - -dependent CNSL 503 CNSL 503 Systematic sampling is more ____ that simple random sampling. - -efficient What kind of problem can arise in systematic sampling? - -someone finds out and avoids being the 5th person Stratified sampling - -dividing the population into strata and randomly sampling from each stratum Example of stratified sampling - -dividing population into age groups and randomly sampling from each stratum Stratified sampling can be hard with... - -large populations Cluster sampling - -dividing the population into clusters and randomly sampling several clusters, then study every member within the cluster Example of cluster sampling - -nursing students taking stats, randomly sample number of counties and sampling students in those counties Convenience sampling - -selecting a sample that is convenient and easy to access Example of convenience sampling - -left handers at school, go into a large lecture hall and everyone left handed raises hand Does convenience sampling result in a representative sample? - -no Convenience sampling is generally more prone to ____ than other sampling. - -bias Sampling statistics is just an ____ of the population and is not ____. - -estimate; exact Sampling error - -discrepancy between population parameter and the sample statistic Sampling error does not mean ____ and there will always be ____ ____. - -mistake; sampling error It is impossible to ____ sampling error, but it is best to ____ it as much as possible. - eliminate; reduce ____ sampling error, ____ accuracy. - -increase; decrease How do you reduce sampling error? - -1. Larger sample size, the smaller the sampling error 2. Use stratified sampling, increases likelihood sample is more representative of the population CNSL 503 CNSL 503 Non-sampling errors or sample bias - -errors that are not the result of random sampling Measurement bias - -may result from a mistake during the measurement process or poorly worded questions Example of measurement bias - -bathroom scales used on carpet rather hard surface Response bias - -when participants respond in a way that is inaccurate or untruthful Example of response bias - -when asking people is arrested, they may not say yes because they don't want to look bad Selection bias - -when the sample is not representative of the population Example of selection bias - -1936 election, people selected to say who they would vote for was taken from people who read the magazine during the great depression, mostly were wealthy people, so it favorited republicans and incorrectly predicted the outcome of the election Distribution of sample means or sampling distribution of the mean - -a frequency distribution of all possible sample means Sampling distribution - -a frequency of distribution of a statistic from every possible sample of a given size n from the population Central limit theorum - -1. The distribution of sample means is approximately normal as long as the sample size is large (n =30+) 2. The mean of all the sample means is equal to the population mean 3. The standard deviation of the distribution of sample means is known as the standard error and is calculation as σ/(squareroot(n)) Standard error - -the average difference between each sample mean and the population mean Standard error indicates... - -how much variability exists between samples Standard error provides as measure of the ____ - -sampling error The larger the standard error, the ____ you would expect the sampling error to be. - larger How do you reduce the standard error? - -increase sample size Probability - -the likelihood of a certain outcome occurring CNSL 503 Outcome - -the possible result of an observation Formula for probability of discrete variables - -p(A)= (number of ways A can happen)/(total number of outcomes) Probability must be between ____. - -0 and 1 0= - -no chance happening 1= - -happens all the time Probability cannot be ... - -negative or greater than 1 Probability is usually reported as a.... - -decimal Probability is the same as.... - -proportion Relative frequency method - -repeating observati