Statistics Review
Quiz yourself by thinking what should be in
each of the black spaces below before clicking
on it to display the answer.
Help!
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| Definitions: |
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| Statistics | the science of collecting, describing, and interpreting data
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| Population | a collection of a set of individuals or objects or events whose properties can be analyzed.
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| Attribute Data | Characteristic
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| Discrete Data | A number that be counted-money
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| Continuous Data | Number that is measureable- time and distance
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| Judgment | Samples that are selected on basics of being typical
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| Probability | Asks about the chance of something specific happening.
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| Random | Every element of a population has an equal probability.
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| Systematic | Every element is selected
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| Stratified | Population is divided into groups
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| Cluster | Divided then groups are sampled
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| Frequency Distribution | a list of data usually put in chart form, that pairs each value of a variable with its frequency.
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| Histogram | bar graph(bars are touching) of a frequency distribution of a quantitive variable.
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| Mean | Average
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| Median | Middle Number
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| Mode | Number that appears most often
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| Range | High - Low
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| Midrange | High + Low / 2
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| Standard Deviation | fluctuation in data.
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| Variance | St. Deviation squared
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| Percentiles | (n)(k)/100
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| Quartiles | value of variables divided by 4 parts
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| 5-number Summary | Divides data into 4 subsets, one quarter of data in each subset
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| Class limit |
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| Class mark | numerical value that is exactly in the middle of each class
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| Class boundary | Values that make up the class
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| Class Width | How spread apart the numbers are
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| Z-score | Value-mean/St.Dev
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| Emperical Rule | If the data is normally distributed then: within st. deviation of the mean there will be approximately 68% of the data
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| Bivariate Data(types) | Attribute or categorical
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| Input variable | independent variable
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| Output variable | dependent variable
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| Scatter Diagram | a plot of all ordered pairs of bivariate data on a coordinate axis-system
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| Correlation Analysis | measure the strength of a linear relationship between two variables
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| Positive and Negative Correlation | +1=perfect positive
-1=perfect negative
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| No Correlation | No relationship between x and y
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| Linear Correlation Coefficient | Numerical measure of the strength of linear relationship between two variables
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| Linear Regression | Finds the equation of the line that best describes the relationship between two variables
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| Equation of the line of best fit: Slope and Intercept |
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| Estimation the line of best fit | Determined by slope and y-intercept
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| Experimental and theoretical probability | Observed relative frequency with which an event occurs value of events A's occurrence
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| Mutually exclusive events | Outcomes in Sample space can never overlap
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| Dependent Events |
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| Independent Events | Two events A + B are independent, if one does not affect the probability assigned to the occurrence of the other.
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| 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.
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| 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.
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| Conditional Probability | the symbol (A/B) represents the probability that A will occur given that B has occurred
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| Addition Rule of Probability | P(A/B)= P(A)+ P(B)-P(A and B)
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| 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)
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| Bayes' Rule | P(A/B)= P(A1) X P(B/A1)/E[P(A1)- P(B/A1)
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You may also shuffle the rows of the table by clicking on the "Shuffle" button.
Or sort by any of the columns using the down arrow next to any column heading.
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