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Stats Final Review

Statistics Review

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