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AP Statistics Summer Vocabulary 2018/19 > Summer Vocab > Flashcards

Summer Vocab Flashcards

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1
Q

What is statistics?

A

the study of variability

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2
Q

what is variability

A

differences. how things differ. there is variability everywhere. we all look different, act different, have different preferences. statisticians look at these differences.

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3
Q

what are 2 branches of AP STATS?

A

inferential and descriptive

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4
Q

what are descriptive stats?

A

tell me what you got! describe to me the data that you collected, use pictures or summaries like mean, median, range, etc…

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5
Q

what are inferential statistics?

A

look at your data, and use that to say stuff about the BIG PICTURE. Like tasting soup, a little sample can tell you a lot about the big pot of soup (population)

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6
Q

Compare descriptive and inferential statistics?

A

descriptive explains you about the data that you have, inference uses the data that you have to say something about the entire population.

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7
Q

what is data?

A

any collected information. generally each little measurement. if it’s a survey about liking porridge, data might be “yes, yes, no, yes, yes”. if the survey is about the number of saltines someone can eat in 30 seconds, the data might be “3,1,2,1,4,3,3,4”

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8
Q

what is a population?

A

the group you’re interested in. sometimes it’s big (all teenagers in the US) sometimes it’s small (all ap stat students at mphs)

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9
Q

what is a sample?

A

a subset of a population. often taken to make inferences about the population. we calculate statistics from samples.

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10
Q

compare population to sample

A

populations are generally large, and samples are subsets of those. we take samples to make inferences about the population. we use statistics to estimate parameters

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11
Q

compare data to statistics

A

data is each little bit of information collected from the subjects. they are the INDIVIDUAL things we collect. we summarize them by for example finding the mean of a group of data. if it is a sample, then we call that mean a “statistic”. if we have data from each member of the population, then that mean is called a “parameters”

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12
Q

compare data to parameters

A

data is each little bit of information collected from the subjects. they are the INDIVIDUAL things we collect. we summarize them by for example finding the mean of a group of data. if it is a sample, then we call that mean a “statistic”. if we have data from each member of the population, then that mean is called a “parameters”

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13
Q

what is a parameter?

A

a numerical summary of a population. like a mean, median, range, of a population

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14
Q

what is a statistic?

A

a numerical summary of a sample. like a mean, median, range, of a sample

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15
Q

we are curious about the average wait time at a dunkin’ donuts drive through in your neighborhood. you randomly sample cars one afternoon and find the average wait time is 3.2 minutes. what is the population parameter? what is the statistic? what is the parameter of interest? what is the data?

A

the parameter is the true average wait time at that dunkin’. this is a number you don’t have and will never know. the statistic is “3.2 minutes”. it is the average of the data you collected. the parameter of interest is the same thing as the population parameter. in this case, it is the true average wait time of all cars. the data is the wait time or each individual car, so that would be like “3.8 min, 2.2 min, .8 min, 3 min” you take that data and find the average, that average is the statistic and you use that to make an inference about the true parameter”

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16
Q

compare data-statistic-parameter using categorical example

A

data are individual measures, like meal preference. “taco, taco, pasta, taco, burger, burger, taco” statistics and parameters are summaries. a statistic would be “42% if sample preferred tacos” and a parameter would be “42% of population preferred tacos”

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17
Q

compare data-statistic-parameter using quantitative example

A

data are individual measures, like how long a person can hold their breath. “45, 64, 32, 68 seconds” that is the raw data. statistics and parameters are summaries like “the average breath holding time in the sample was 52.4 seconds”. and a parameter would be “the average breath holding time in the population was 52.4 seconds”

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18
Q

what is a census?

A

like a sample of the entire population. you get information from every member of the population

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19
Q

does a census make sense?

A

a census is ok for a small population, but impossible if you want to survey “all US teens”

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20
Q

what is the difference between a parameter and statistic?

A

both are a single number summarizing a larger group of numbers, but Parameters come from Populations and Statistics come from Samples

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21
Q

if i take a random sample of 20 hamburgers from five guys restaurant and count the number of pickles on a bunch of them… and one of them had 9 pickles, then the number 9 from that burger would be called….?

A

a data value/ datum

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22
Q

if i take a random sample of 20 hamburgers from five guys restaurant and count the number of pickles on a bunch of them… and the average number of pickles was 9.5, then 9.5 is considered a….?

A

statistic (a summary of a sample)

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23
Q

if i take a random sample of 20 hamburgers from five guys restaurant and count the number of pickles on a bunch of them… and i do this because i wanna know the true average number of pickles on a burger at five guys, the true average number of pickles is considered a….

A

parameter! a one number summary of the population. the truth. aka the parameter of interest

24
Q

what is the difference between a sample and a census?

A

with a sample, you get information from a small part of the population. in a census, you get info from the entire population. you can get a parameter from a census, but only a statistic from a sample.

25
Q

use the following words in one sentence: population, parameter, census, sample, data, statistic, inference, population of interest.

A

i was curious about a population parameter, but a census was too costly so i decided to choose a sample, collect some data, calculate a statistic and use that statistic to make an inference about the population parameter/ the parameter of interest

26
Q

if you are tasting soup, then the flavor of each individual thing in the spoon is the ______, the entire spoon is a _____, the flavor of all that stuff together is like the_____ and you use that to _____________ about the flavor of the entire pot of soup, which would be the _______.

A

data, sample, statistic, make an inference, parameter.

27
Q

what are random variables?

A

if you randomly choose people from a list, then their hair color, height, weight, and any other data collected from them can be considered random variables.

28
Q

what is the difference between quantitative and categorical variables?

A

quantitative variables are numerical measures, like height and IQ, categorical are categories, like eye color and music preference

29
Q

what is the difference between quantitative and categorical data?

A

data is actually gathered measurements. data from categorical variables are usually words. data from quantitative variables are numbers

30
Q

what is the difference between discrete and continuous variables?

A

discrete can be counted. like number of cars (1,2,3,4) and continuous is something like weight of a mouse (4.344 ounces)

31
Q

what is a quantitative variable

A

quantitative variables are numeric like height, age, number of cars sold, SAT score…. etc

32
Q

what is a categorical variable?

A

qualitative variables are like categories: blonde, listens to hip hop, female, yes, no… etc

33
Q

what do we sometimes call a categorical variable

A

qualitative

34
Q

what is quantitative data?

A

the actual numbers gathered from each subject. 211 pounds, 67 beats per minute

35
Q

what is categorical data?

A

the actual individual category from a subject, like “blue” or “female” or “sophomore”

36
Q

what is a random sample?

A

when you choose a sample by rolling dice, choosing names from a hat, or other real randomly
generated sample. humans can’t really do this well without the help of a calculator, cards,
dice, or slips of paper

37
Q

what is frequency?

A

how often something comes up

38
Q

data or datum?

A

datum is singular. data is plural.

39
Q

what is a frequency distribution?

A

a table, or a chart that shows how often certain values or categories occur in a data set

40
Q

what is meant by relative frequency?

A

the percent of time something comes up (frequency/total)

41
Q

how do you find relative frequency

A

divide frequency by total

42
Q

what is meant by cumulative frequency?

A

add the frequencies as you go.

43
Q

make a guess as to what relative cumulative frequency is?

A

the added up percentages. always end at 100%

44
Q

what is the difference between a bar chart and a histogram?

A

bar charts are for categorical data (bars don’t touch) and histograms are for quantitative data (bars touch)

45
Q

what is the mean?

A

the old average we used to calculate. it is the balancing point of the histogram

46
Q

what is the difference between a population mean and a sample mean?

A

population mean is the mean of a population, a parameter. sample mean is a mean of a sample so it is a statistic. we use sample statistics to make inferences about population parameters

47
Q

what symbols do we use for population mean and sample mean?

A

Mu for population mean (parameter) x-bar for sample mean (statistic)

48
Q

how can you think about the mean and median to remember the difference when looking at a histogram

A

mean is balancing point of histogram, median splits the area of the histogram in half

49
Q

what is the median?

A

the middlest number, it splits area in half (always in the position n+1 divided by 2)

50
Q

what is the mode?

A

the most common. the peaks of the histogram. we often use mode with categorical data

51
Q

when do we often use mode?

A

with categorical variables. for instance, to describe the average teenagers preference, we often speak of what “most” students chose, which is the mode. it also tells the number of bumps in a histogram for quantitative data (unimodal, bimodal)

52
Q

why don’t we always use mean, we’ve been calculating it all of our life?

A

it is not resilient. it is impacted by skewness and outliers

53
Q

when we say the “average teenager” are we talking about mean, median, or mode?

A

it depends. if we are talking about height, it might be the mean. if we are talking about parental income, we’d probably use the median. if we are talking about music preference, we’d probably use the mode.

54
Q

what is a clear example of where the mean would change but median wouldnt?

A

if we asked 8 people how much money they had in their wallet. the mean of the set is 5, and the median is also 5. you might say “the average person in this group has $5” but imagine if one of them just got back from the casino and had $9000, in this case the median would still be 5 but the mean goes up to over $1000.

55
Q

how are the mean, median and mode positioned in a skewed left histogram?

A

goes in that order from left to right. mean, median, mode

56
Q

how are the mean, median and mode positioned in a skewed right histogram?

A

in the opposite order. mode, median, mean

57
Q

who chases the tail?

A

the mean chases the tail

AP Statistics Summer Vocabulary 2018/19 (1 decks)

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