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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) |
Created by:
kk_taki2
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