- Print the notecards
- Fold each page in half along the solid vertical line
- Cut out the notecards by cutting along each horizontal dotted line
- Optional: Glue, tape or staple the ends of each notecard together

front 1 Descriptive statistics | back 1 Methods that ehlp researchers organize, summarize, and simplify the results obtained from research studies - Organizing a set of scores into a graph or a table, calculating average score |

front 2 Inferential statistics | back 2 Use information from samples to answer general questions about populations, help researchers determine when it is appropriate to generalize from a sample to a populations |

front 3 Statistic | back 3 A summary value that describes a sample such as the average score of a sample - Describe the entire set of scores in the sample - Provide information about the corresponding summary values for the entire population |

front 4 Parameter | back 4 A summary value that describes a population such as the average score for a population |

front 5 Descriptive statistics techniques | back 5 - Organize the entire set of scores into a table or a graph that allows researchers to see the whole set of scores - Compute one or two summary values (such as the average) that describe the entire group |

front 6 Frequency distribution | back 6 Consists of a tabulation of the number of individuals in each category on the scale of measurement - Shows the set of categories that make up the scale of measurement and the number of individuals with scores in each of the categories |

front 7 Histogram | back 7 Shows a bar above each score and the height of the bar indicates the frequency, the bars for adjacent scores touch each other. - Used for interval or ratio scale of measurement |

front 8 Polygon | back 8 Shows a point above each score so that the height of the point indicates the frequency, straight lines connect the points and additional straight lines are drawn down to the horizontal axis at each end to complete the figure - Used for interval or ratio scale of measurement |

front 9 Bar graph | back 9 Like a histogram except that a space is left between adjacent bars - Used for nominal or ordinal scales |

front 10 Central tendency | back 10 A statistical measure that identifies a single score that defines the center of distribution, goal is to identify a value that is most typical |

front 11 Mean | back 11 Arithmetic average of the data, usually obtained from an interval or ratio scale of measurement |

front 12 Median | back 12 The score that divides the distribution in half, works well for nominal scales |

front 13 Mode | back 13 The score with the greatest frequency - bimodal: two distinct modes - multimodal: more than two modes |

front 14 Variability | back 14 Describes the spread of scores in a distribution, small when the scores are all clustered together |

front 15 Variance | back 15 Measure variability by computing the average squared distance from the mean. - Measure the distance from the mean for each score - Square the distances - Find the sum of the squared distances and divide by n-1 (degrees of freedom) |

front 16 Standard deviation | back 16 The square root of the variance and provides a measure of variability by describing the average distance from the mean - 70% within one SD - 95% within two SD |

front 17 Factorial research studies | back 17 Include two ore more independent variables |

front 18 Correlation | back 18 Measures and describes the relationship between two variables - Indicates direction of relationship - Form of the relationship is determined by the type of correlation - Pearson correlation (r): evaluates linear relationships - Spearman correlation (r - Strength of relationship is described by the numerical value of the correlation |

front 19 Regression | back 19 The process of finding the linear equation (regression equation) for the straight line that provides the best fit for the data points |

front 20 Linear equation | back 20 Y = bX + a - b: slope constant - a: y-intercept (point at which the line intersects the Y axis - Standardized version (X and Y transformed into z-scores): z - Average amount of error directly correlated to the value of Pearson correlation (+/-1.00 = average error is small) - Squared value of correlation (r |

front 21 Multiple regression | back 21 The process of finding the most accurate prediction equations with multiple predictors |

front 22 Multiple regression equation | back 22 Y = b - R |

front 23 Sampling error | back 23 The naturally occurring difference between a sample statistic and the corresponding population parameter |

front 24 Hypothesis test | back 24 A statistical procedure that uses sample data to evaluate the credibility of a hypothesis about a population, attempts to rule out chance as a plausible explanation for the results |

front 25 Null hypothesis | back 25 A statement about a population and always says that there is no relationship, specifies what the population parameter should be if nothing happened |

front 26 Sample statistic | back 26 Data from the research study are used to compute the sample statistic corresponding to the parameter specified in the null hypothesis |

front 27 Standard error | back 27 A measure of the average, or standard, distance between a sample statistic and the corresponding population parameter |

front 28 Test statistic | back 28 A mathematical technique for comparing the sample statistic with the null hypothesis, using standard error as a baseline. Test statistic = (sample statistic - parameter from null)/ standard error = actual difference between data and hypothesis/difference expected by chance - 1.00 = null hypothesis true - >1.00 = null hypothesis rejected |

front 29 Alpha level (level of significance) | back 29 The maximum probability that the research result was obtained simply by chance, a smaller level means you have more confidence - Alpha level of .01 means the test demands that there is .01 probability that the results are caused only by chance - Can be expressed as p<.05 |

front 30 Statistically significant result | back 30 It is extremely unlikely that the research result was obtained simply by chance, always accompanied by an alpha level that defines the maximum probability that the result is caused only by chance. |

front 31 Type I Error | back 31 Occurs when the sample data appear to show a significant effect but there is no effect in the population, occurs when an extreme sample is selected |

front 32 Type II Error | back 32 Occurs when sample data do not show evidence of a significant effect when a real effect does exist in the population |