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# Stats Final Review

### Statistics Review

Question | Answer |
---|---|

Definitions: | |

Statistics | the science of collecting, describing, and interpreting data |

Population | a collection of a set of individuals or objects or events whose properties can be analyzed. |

Attribute Data | Characteristic |

Discrete Data | A number that be counted-money |

Continuous Data | Number that is measureable- time and distance |

Judgment | Samples that are selected on basics of being typical |

Probability | Asks about the chance of something specific happening. |

Random | Every element of a population has an equal probability. |

Systematic | Every element is selected |

Stratified | Population is divided into groups |

Cluster | Divided then groups are sampled |

Frequency Distribution | a list of data usually put in chart form, that pairs each value of a variable with its frequency. |

Histogram | bar graph(bars are touching) of a frequency distribution of a quantitive variable. |

Mean | Average |

Median | Middle Number |

Mode | Number that appears most often |

Range | High - Low |

Midrange | High + Low / 2 |

Standard Deviation | fluctuation in data. |

Variance | St. Deviation squared |

Percentiles | (n)(k)/100 |

Quartiles | value of variables divided by 4 parts |

5-number Summary | Divides data into 4 subsets, one quarter of data in each subset |

Class limit | |

Class mark | numerical value that is exactly in the middle of each class |

Class boundary | Values that make up the class |

Class Width | How spread apart the numbers are |

Z-score | Value-mean/St.Dev |

Emperical Rule | If the data is normally distributed then: within st. deviation of the mean there will be approximately 68% of the data |

Bivariate Data(types) | Attribute or categorical |

Input variable | independent variable |

Output variable | dependent variable |

Scatter Diagram | a plot of all ordered pairs of bivariate data on a coordinate axis-system |

Correlation Analysis | measure the strength of a linear relationship between two variables |

Positive and Negative Correlation | +1=perfect positive -1=perfect negative |

No Correlation | No relationship between x and y |

Linear Correlation Coefficient | Numerical measure of the strength of linear relationship between two variables |

Linear Regression | Finds the equation of the line that best describes the relationship between two variables |

Equation of the line of best fit: Slope and Intercept | |

Estimation the line of best fit | Determined by slope and y-intercept |

Experimental and theoretical probability | Observed relative frequency with which an event occurs value of events A's occurrence |

Mutually exclusive events | Outcomes in Sample space can never overlap |

Dependent Events | |

Independent Events | Two events A + B are independent, if one does not affect the probability assigned to the occurrence of the other. |

Law of Large Numbers | If the # of times an experiment is increased, the ratio of the # of successful occurrences is the number of trials tend to approach the theoretical probability of the outcome of trial. |

Complement of an event | the set of all sample points in the sample space that doesn't belong to event A. The complement of Event A is denoted by A. |

Conditional Probability | the symbol (A/B) represents the probability that A will occur given that B has occurred |

Addition Rule of Probability | P(A/B)= P(A)+ P(B)-P(A and B) |

Multiplication Rule of Probability | P(A and B)=P(A)X P(B/A) or P(A and B)= P(B)X P(A/B) |

Bayes' Rule | P(A/B)= P(A1) X P(B/A1)/E[P(A1)- P(B/A1) |