ANSC 3011 Exam 1Questions And Answers Verified Solutions| Graded A+.

Statistics - correct answer classification, analysis and interpretation of data collection of procedures/principles to gain & process info to make decisions when faced w/ UNCERTAINTY Other names for animal statistics - correct answer biostatistics, biometrics, biometry (stat methods applied to biosciences) Why's Statistics Important? - correct answer - we're bombarded w/ statistical info; don't want to take info on face-value - stats is used to affect public opinion - info can be easily misinterpreted, manipulated, invalid With Statistical Knowledge, you are able to: 1. 2. 3. - correct answer 1. question stats provided 2. decide if data is credible 3. decide if data will influence your current or future decisions By the end of this course you should: - correct answer - understand the importance of data and the source of data - be skeptical/not jump to conclusions - interpret stat results & come up with your own conclusions - understand diff b/t stat significant and biological relevance Statistical Significance DOES NOT indicate: - - - - correct answer - magnitude - relevance - happenings by chance Data - correct answer records of measurements & counts of observations Variable - correct answer characteristic of a subject ex: calf body weights, feed per gain in pigs, breed of horses Variables can be classified as: - correct answer quantitative numeric - body weight, age, feed intake, time, temp, litter size, egg count categorical qualitative - ex: eye color, pregnancy status (open vs pregnant), BCS Population - correct answer entire group about which researchers want information - represents all members of a certain group or category of interest Sample - correct answer subset of the larger population 2 ways to find average milk production of dairy cows at dairy barn: - correct answer - measure all cows at dairy barn (population) - randomly select subset of dairy cows (sample) Parameter vs Statistic - correct answer Parameter (p): - mean calculated from a population - number that describes a POPULATION (fixed number) - value usually unknown Statistic (p-hat): - mean calculated from sample - not a fixed number (changes from SAMPLE to sample) - value is known Is a sample always a good representation of the population? - correct answer no 2 methods to collect data - correct answer 1. Observational Studies (surveys, polls, questionnaires, watch & record) 2. Experimental Studies (impose or apply treatment & measure response) Observational Studies - correct answer - unobtrusive (no treatment applied, ex situ) - surveys, questionnaires, watching & recording What type of data collection method is a census? - correct answer it's a survey of human population, so observational studies Experimental Study - correct answer deliberately impose or apply a treatment and measure the response Treatment - correct answer specific experimental condition applied to subjects ex: impact of hormones on cell processes, effect of feed additives on growth rates of animals extrapolation - correct answer when you infer from a sample to a population, and the sample is NOT representative of the entire population - try not to generalize results of sample to large population not even represented in a population Descriptive Staistics - correct answer applies to the sample from which data has been collected Inferential Statistics *** - correct answer refer to teh use of a sample data to reach a conclusion (make a inference) about larger population the sample is supposed to represent good vs bad sampling - correct answer Good: - random sampling Bad: - convenience sampling (ex: if you always sampled from the top, results will be biased) - voluntary response (creates biased results) Biased - correct answer systematically favor certain outcomes Convenience Sampling - correct answer selection on the basis of proximity At a shopping mall, you are asked to participate in a consumer survey. good or bad sampling? - correct answer bad - people shopping at mall most likely not representative of entire US Interviewers want to hire people that seem more approachable. What type of sampling is this? - correct answer convenience sampling Undercoverage - correct answer when part of the population has no chance to be selected Ex: Sampling Frame - correct answer list used to select subjects in the target population. if certain group of population is excluded from sampling frame, random sample from the frame will be bias SRS - correct answer simple random sampling - give every individual and every sample an equal chance to be chosen *chosen purely by chance ex of small vs large samples - correct answer small: select subjects using names from a hat large: random # generator or table of random digits Systematic sampling - correct answer first subject from a list of the population is selected then each nth subject on list is selected - trait coinciding w/ sample technique could = bias Error - correct answer deviation b/t sample statistic and population parameter (fixed number that describes a population) Sampling error can: - correct answer result in biased results increase variability in your sample sources of error in sampling: - correct answer sampling methodology non-sampling error (error not associated w/ process of taking sample) ex of sources of error - correct answer convenience sampling voluntary sampling why would convenience sampling and voluntary sampling be used? - correct answer quick inexpensive convenient usually = biased results processing error: - correct answer mistakes made when entering or processing data - can increase variability or result in bias same rounding error result in increased variability or increased bias? - correct answer increased bias mistakes when tired while entering in data result in increased variability or increased bias? - correct answer increased variability response error causes? - correct answer false or incorrect answer is given due to: - personal questions - sensitive issues - misunderstand question - remember incorrectly - pressed for time Non-sampling errors - correct answer can increase variability or result in bias