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Statistics Test 2
Collecting data
| Question | Answer |
|---|---|
| Population: | The entire group we want information about |
| Sample: | A REPRESENTATIVE of the population |
| What do we want the sample to be? | (blank) |
| What is an important characteristic of a random sample? (The Most Important) | Each item must have an equal change of being selected |
| Observational Study: | We just observe individuals and measure variables of interest, we don't influence a response |
| Experiment: | The researcher imposes a treatment on individuals to observe response. Usually COMPARES |
| What is the goal of randomization? | create groups that are as similar as possible before treatments |
| What does normalization or having a bell shaped curve imply? | randomization, having similar groups |
| What is blocking? | Seperating objects into similar groups so no confounding occurs |
| When is an event considred random? | individual outcomes are uncertain, but pattern emerges in long run |
| What is probability? | Measures the likelihood of a random event |
| Relate probabilty and randomness to a coin toss | A coin toss is random because in the long run, we expect a 50% distribution, so the probability of this is 0.5 because we expect about half of coin tosses to be heads |
| Parameter: | Any number that describes a population |
| Statistic: | Any number that describes a sample |
| What is important to note about parameter-population and statistic-Sample? | The first letters match and that's how to remember them |
| What are the two concepts most important to note about probability? | Individual outcomes are uncertain, a pattern emerges in long run |
| What is the sampling distribution of a statistic? | Distribution of all possible values the statistic could have in all possible samples of same size and population |
| What is the Central Limit Theorem? | Provided that n is large, the sample will have a normal distribution with the same mean as original distribution and s.d = sigma/radical n |
| WE DON'T REALLY CARE ABOUT POPULATION DISTRIBUTION | (blank) |
| What is a simple Random Sample? | Two steps 1)Label everyone 2) Use Table B |
| Bias: | Favors certain outcomes |
| What are the types of bias? | Voluntary sample and convenience sample |
| Treatment: | Experimental condition applied to subjects |
| Comparative experiment: | Compares two groups |
| Control: | Receives sham treatment |
| Why are experiments better than obsevational studies? | Observational studies can have lurking variables to cause confounding |
| Probability sample: | A known chance over zero of being selected |
| Stratified Random Sample: | Divide population into groups of similar individuals (strata), choose SRS from strata, combine for full sample |
| Factors: | Explanatory variables (dose of drug) |
| Level: | Subdivision of factor |
| Randomization | Use chance to divide experimental units into groups |
| What is the logic of Randomized Comparative Experiments | 1) Random assignment = groups similar in all respects b4 test 2) Comparative design = outside influences equal to all groups 3) Differences in average response due to treatment or play of chance in the random assignment of subjects to treatments |
| What are the three principles of experimental design: | Control (lurking variables) 2)Randomization 3)Replication (more tests less chance of variation) |
| Block: (Example) | Experimental units or subjects known to be similar enough to affect response to treatment prior to experiment's run (Luxury cars) |
| Matched pairs: | Common form of blocking for comparing two treatments |
| Sampling Variablility: | Statistic varies in repeated random sampling |
| Law of large numbers: | Random observations from any population with finite mean (u). As observations increase, the mean X of the sample gets closer to mean U of population |
| What does sampling distribution mean in ENGLISH | Ideal pattern that would emerge if we looked at all possible samples of n we take. |
| Four aspects of Sampling distributions: | 1)Identify parameters and statistics in a sample or experiment 2) Recognize sampling variability: different values after repetition 3)Describes values taken by statistic in all possible repetions under same conditions 3)describe problites of possible valu |
Created by:
talkglitter2486