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# Quantitative

Answer | |
---|---|

independent variables | researcher manipulates/researcher can assign you/ cause (not result) |

dependent variable | measuring behavior/ result (not cause) |

correlation | 2 variables that are related |

population | complete collection of anything regardless of size |

sample | subset of population/ measure so we can talk about population |

parameter | numerical summary characteristics of a population stuff you can measure about a population |

statistics | numerical summary of characteristics of a sample |

nominal scale (scale of measurement) | assigns names or label to objects or events not related numerically just assigned |

ordinal scale (scale of measurement) | puts objects/events in RANK order the difference btwn 1&2 doesn't mean anything just the order is meaningful |

interval (scales of measurement) | equal intervals btwn numbers rank & equal distance zero isn't true zero, its a point on a scale |

ration (scales of measurement) | zero means absence of what your measuring true zero absolute 0 degrees K no heat height 0.00 inches quantity/time |

frequency distribution | create a table of the data gives organization table shows # of times a given score/ group of score occurs |

rules of graphing | x= variable being studied y-axis=should be 3/4 the the length of the x-axis *always be divided using full range of frequency *always begin y-axis at zero *if your using top half, indicate a break |

bargraph | histogram but bars dont touch |

histogram | depicts grouped frequency distribution |

grouped frequency distribution | range grouped data |

central tendency | trying to come up with 1 number to describe variables mode mean median |

mode | most frequently occurring score in a group of scores x |

median | score that separates top half of group of scores from bottom half normal curve-median & mode in same place *data has to be in order middle score |

percentile | score at or below which a given percentage of the scores lie 50th percentile: 50% of score are below that score |

mean | arythmetic average/ sum of scores divided by number of scores (sum)(x-score)/N-number |

mean properties | if you take all score the sum of the difference between each score and mean will be 0 sum of squared differences btwn each score from mean will be smaller than sum of squared diff. of any score 1,2,3,4,5 5-3=2 4-3=1 3-3=0 3-4=-1 3-5=-2 |

z-score | aka standard scores the deviation of the raw from the mean in standard deviation units z=raw score(x)-(mean)/SD |

probability | the probability of event occurring is proportion of times event would occur if chance of occurrence were infinite |

statistical hypothesis | hyp- guess about population based on sample results use probability theory to determine degree of certainty we have abt experimental results |

2 rules of probability | 1. each event independent from each other/ stand alone. necessary for simple probability 2. dice or coin dont have memory and cant remember or keep track |

gamblers phallacy | (wrong belief) mistaken belief that probability of particular event changes with long strain of some event i.e. slot machines |

addition rule | mutually exclusive random events compute the probability of one OR the other occurring P(A or B)= PA + PB 2 of spaids or 3 of clubs 1/52 + 1/52 = 2/52 = 1/56 |

multiplication rule | probability of 2 or more independent events occurring is the product of individual probabilities P rolling 2 ones (snake eyes) (1/6) (1/6) = 1/36 |

non independent events | *conditional probability drawing card and holding onto it draw ace and draw another one (4/52)(3/51)=1/221= .0045= .45% probability of second dependant on first |

confidence interval | specific kind of interval estimate interval estimate of population can define by how "confident" compute a way to estimate things about a population |

interval | range (set) of numbers |

sampling distribution of mean | distribution of means of many samples u= mean of population |

sampling distribution of mean (rules) | 1. if you have infinite #, mean of means would be u 2. the more samples you get, the more the frequency graphs will look like normal curve 3. SD of means= standard error of mean 4. the larger each sample size, the smaller the standard error of mean |

central limit theorem | the more samples you get, the more the frequency graphs will look like normal curve |

t-score | how far a group mean is from population mean in standard error units |

variable | anything that can take on different values or amounts |

Created by:
frankiegym