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11 Cards in this Set

  • Front
  • Back

Statistical Inference

- Using a random sample to draw conclusions about a population parameter

Discrete Probability Distribution

- A collection of values of a discrete random variable along with their corresponding probabilities


- Usually expressed in the format of a graph, table, or formula


- Has 2 mathematical conditions that must be met 1. ∑P(x) = 1 2. 0 ≤ P(x) ≤ 1


Histogram

- A bar graph in which the horizontal scale represents classes of quantitative data values and the vertical scale represents frequencies.


- The heights of the bars correspond to the frequency values, and the bars are drawn adjacent to each other without gaps.


- Best graph to see the "shape" of the data.


- Able to see how much variation there is in data. A histogram with a lot of variation will be wider than a histogram with less variation, assuming we are measuring items in the same units/scale


- Also used to see outliers.

Pareto Chart

- A bar graph for qualitative data, with the bars arranged in order according to frequencies.


- Vertical scales can be frequencies or relative frequencies.


- The tallest bar is always placed at the left in a pareto chart with subsequent bars in descending order.


- Often used to identify the largest source of problems.


Why is probability distribution important in stats?

- They are used to model "the behavior" of random variables.

Experiment

- Apply some treatment and then observe its effects on subjects.


- Subjects in experiments are called experimental units.


- Harder and takes more time / $ but better than observational study

Observational Study

- Observing and measuring specific characteristics without attempting to modify the subjects being studied.

Qualitative Data

- Data that consists of names or labels (representing categories)


- Also called categorical or attribute data


- I.E. Genders or shirt #s on pro athletes uniforms to replace name

Quantitative Data

- Data that consists of numbers representing counts or measurements.


- I.E. the weight of supermodels or the ages of respondents

Statistic

- Numerical summery of a sample.


- Sample -> Statistic


Parameter

- Numerical summary of population data.


- Population -> Parameter