Flashcards in CH 1 Deck (39):

1

## Statistics

### Numerical summary of a sample

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## Descriptive statistics

### Organizing and summarizing data

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## Inferential statistics

### Methods that take a result form a sample, extend it to the population, and measure the reliability of the result.

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## Parameter

### Numerical summary of a population

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## Popoulation

### Entire group in study

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## Sample

### Subset of the population being studied

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## Qualitative varible

### Can be classified based on attribute or characteristic

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## Quantitative variable

### Numerical measure of an individual

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## Discrete quantitative variable

### Countable, finite number of possible values

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## Continuous quantitative variable

### Infinite number of possible values. Can take on every possible value between any two values.

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## Nominal variable

### Names, labels, or categorizes

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## Ordinal variable

### Nominal + must have level of ranking or specific orders

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## Interval variable

### Ordinal + differences in values of variables

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## Ratio variable

### Interval + clear definition of zero (none of something)

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## Observational Study

### Measures the value of the response variable without attempting to influence the value of either the response or explanatory variables.

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## Experiment

### Intentionally change the value of the explanatory variable to record the responses of each group.

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## Cross-sectional studies

### Collect information at a specific point in time, or over a very short period of time.

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## Case-control studies

### Retrospective. Look back in time or look at existing records. Individuals with certain characteristics are matched with those who do not have it.

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## Cohort Studies

### the cohort = the group to be studied. They are observed over a long period of time = Prospective study.

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## Response variable

### What is being studied

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## Explanatory variable

### What is affecting the response variable

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## Confounding

### when the effects of two or more explanatory variables are not separated. Could lead to different conclusions about the results.

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## Lurking variable

### An explanatory variable that was not considered in a study, but that affects the value of the response variable in the study. Typical related to explanatory variables.

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## Random Sampling

### Process of using chance to select individuals form a population to be included in the sample

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## Sample without replacement

### Individual who is selected is removed from the population and cannot be chosen again.

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## Sample with replacement

### Selected individual is placed back into the population and could be chosen a second time.

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## Simple Random Sampling

### A sample of size n from a population of size N is obtained through simple random sampling if every possible sample of size n has an equally likely chance of occurring.

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## Stratified sample

### Obtained by separating the population into non overlapping groups and then obtaining a simple random sample from each group

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## Systematic sampling

### Obtained by selecting every "k"th individual from the population (first individual is selected randomly from 1 to k)

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## Cluster sampling

### Obtained by selecting individuals within a randomly selected group of individuals.

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## Convenience sampling

### Sample in which the individuals are easily obtained

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## Systematic formula when k is known

###
p + (n-1)k

p = first client

n = sample size

k = every "k"th individual

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## How to find "k"th individual in systematic sample when N/n is known.

###
N/n

N = total population

n = desired sample size

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## Sampling bias

### When the technique used to sample favors one part of the population over another.

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## Under coverage

### proportion of one segment of the population is lower in a sample than the population

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## Response bias

### When answers on a survey do not reflect the true feelings of the respondent.

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## Inherent bias

### Inability to measure accurately and directly what one would wish to measure.

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## Matched-pair design (experiment)

### Experimental units are paired up. Where one individual will receive one treatment and the other receives a different one. aka Pre and post experiment

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