Help
Options
Didn't know it?
click below
click below
Knew it?
click below
click below
Don't Know
Remaining cards (0)
Know
retry
shuffle
restart
0:00
Embed Code - If you would like this activity on your web page, copy the script below and paste it into your web page.
Normal Size Small Size show me how
Normal Size Small Size show me how
STATS VOCAB TEST 1
| Term | Definition |
|---|---|
| statistics | science of collecting, organizing, analyzing, and summarizing data to answer questions and draw conclusions |
| data | another word for information |
| population | entire group being studied (unlimited, specific) |
| sample | any subset from the population (as large as possible, as unbiased as possible) |
| parameter | data collected and analyzed from a population, a measure |
| statistic | data collected and analyzed from a sample |
| descriptive statistics (branch 1) | consists of collecting and organizing data to describe what is seen |
| inferential statistics (branch 2) | uses methods of analysis and probability to take results from a sample and extend them to answer questions about a population and a future |
| variable | any characteristic of the population that can take on a random outcome |
| ordinal variable | those with a natural order ex:letter grades |
| nominal variable | those with no order ex: hair color, brands |
| quantitive statistics | those that are numerical ex: age, height, weight, how many of something |
| discrete variables | those that are countable |
| continuos variables | those that are uncountable ex: height, temperature, blood pressure - note that these are usually tedious and resorting straight to a graph is usual |
| observational study | a researcher merely observes what is happening to answer questions (no manipulation) |
| hawthorne effect | do we change our behavior when we know we are being studied/watched? |
| experimental study | a researcher manipulates and looks to see how this affects other variables |
| lurking variables | those that effect the outcome of an experiment, but arent being studied by the researcher |
| qualitative variables | those that can be arranged into categories ex: hair color, martial status, brands, letter grades |
| raw data | merely collected data with no order or arrangement |
| frequency distribution | a table that arranges data into class with their frequency (NOMINAL DATA) ex: blood type |
| pareto chart | bar graph with bars in decending order of frequency |
| pie chart | circular graph with classes represented as wedges of the circle |
| bar graph | bars in class order (ORDINAL DATA) |
| dot plot | number line with data representing data value |
| grouped classes | used when the data values vary to much, open ended classes help to summarize the data |
| cumulative frequency (c.f) | the accumulation of frequencies as we go down the table |
| histogram | bar graph for continious data in which bars are arranged according to the number line |
| stem and leaf plot | a vertical graph that cuts the data value into two pieces |
| truncate | to cut off without rounding ex: 3120- 31 4210- 42 |
| open ended class | this is a class that includes more than one value, or an open ended value open to both the low and high end ex: 7+ or 3+ |
| grouped frequency distributions | uses classes of grouped intervals of data |
| cumulative frequency | this is the sum of frequencies as we go down the table (note that you would not use this for categories) |
| histogram shapes | 1. bell shaped 2. uniform 3. skewed (to the left or the right) 4. bimodal 5. U shaped |
| measure | any calculation performed on a data set |
| measures of central tendency | calculates the center of a data set |
| mean | (arithmetic average)- the sum off all data values / the total number of data points |
| median | middle value when the data is in order |
| mode | value that occurs most often (can be 0, 1, or more) ex: "the average hair color is brown" |
| midrange | quick measure of the sum of the high and low divided by 2 (old method) |
| weighted mean | used when different data values have different levels of importance ex: GPA |
| percentiles | cut a data set into 100 equal intervals ex: 43rd percentile means that the data value is above 43% of other values, and below 57% of all other values |
| quartile | cut a set of data into 4 equal intervals |
| 5 number summary | includes the datas (in order) low, Q1, Q2, Q3, and the high ex: 1, 2, 2, 5, 6, 7, 8, 8, L- 1 Q1- 2 Q2- 5.5 Q3- 7.5 H- 8 |
| z scores | a measure that shows a data values distance away from the mean (used when comparing unrelated data) |
| measures of position | these measures compare 1 data value to the rest of the set |
| outlier | an extremely high or low data value compared to the rest of the set (sometimes an oddball or mistake) |
| range | measure of variation that is found by subtracting the low value from the high value |
| variance | the mean of the squared distances of the data value fall away from the mean |
| standard deviation | squared root of the mean, of the squared distances of the data value, away from the mean |
| chebyshevs rule | for any set of data, at least (1-1/k2)100%, of the data values will fall within k standard deviations of the mean |
| empirical rule | (ONLY BELL SHAPED DATA) 68, 95, 99 |
| measures of correlation | you have two sets of data. Is there a relationship? 1st variable- x (independent or explanatory, variable being manipulated) 2nd variable- y (dependent or resultant variable) |
| scatter diagram | xy graph that plots each pair of data values as points to look for a pattern types: positive linear, negative linear, non linear, none |
| correlation coefficient | measure of the linear strength of the relationship between 2 variables |
| least square regression line | this is the line of best fit for representing the correlation of the data |
| Beyond The Scope of Study | the study represents a curtain sample of people and data, the correlation should not be extended too far beyond them, do not extrapolate too much!) |
Created by:
user-1765866