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AP Stats > Summer Work > Flashcards

Summer Work Flashcards

1
Q

What is Statistics?

A

the study of variability

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2
Q

what is variability?

A

differences… how this 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 stats?

A

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

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6
Q

compare descriptive and inferential stats

A

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

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7
Q

what is data?

A

any collected information. generally each little measurement… like if it a survey about liking porridge… the data might be “yes, yes, no, yes, yes” if it is 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 are interested in. sometimes it’s big like “all teenagers in the US” other times it’s small like “all AP Stats students in my school”

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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 small subsets of these populations. we take samples to make inferences about populations. 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 little 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 a population, then that mean is called a “parameter”

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12
Q

compare data to parameters

A

(2)data is each little bit of information collected from the subjects… they are the INDIVIDUAL little 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 a population, then that mean is called a “parameter”

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13
Q

what is a parameter

A

a numerical summary of a population. like a mean, median, rage… of a population

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14
Q

what is a statistic?

A

a numerical summary of a sample. Like 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-thru 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’ donuts. 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 of each individual car, so that would be like “3.8 min, 2.2 min, .8 min, 3 min.” you take that data and fine the average, that average is called a “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, taco” … statistics and parameters are summaries. a statistic would be “42% of 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 measurements, like how long a person can hold their breath “45 sec, 64 sec, 32 sec, 68 sec.” this is the raw data. statistics and parameters are summaries like “the average breath holding time in the sample was 52.4 sec” and a parameter would be “the average breath holding time in the population was 52.4 sec”

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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 okay for small populations but impossible if you want to survey all US teens

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20
Q

what is the difference between a parameter and a statistic?

A

BOTH ARE A SINGLE NUMBER SUMMARIZING A LARGER GROUP OF NUMBERS… but PPPARAMETERS come from PPPOPULATIONS… SSSTATISTICS come from SSSAMPLES

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21
Q

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

A

a datum or data value

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22
Q

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

A

a statistic

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23
Q

if i take a random sample of 20 hamburgers from five guys and count the number of pickles on a bunch of them and i do this because i want to know the true average number of pickles on a burger at five guys, the true average number of pickles is considered a what?

A

a parameter, 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, statistics, inference, population of interest

A

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

26
Q

if you are tasting the 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

if you are tasting the soup then the flavor of each individual thing in the spoon is the DATA the entire spoon is a SAMPLE the flavor of all that stuff together is like the STATISTIC and you use that to MAKE AND INFERENCE about the flavor of the entire pot of soup which would be the PARAMETER. notice you are interested in the parameter to begin with… that is why you took a sample.

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

30
Q

what is the difference between quantitative and categorical data?

A

the data is the actual gathered measurements so if it is eye color, then the data would look like this “blue, brown, brown, brown, blue, green, blue, brown… etc.” the data from categorical variables are usually words often it is simply “yes, yes, yes, no, yes, no” if it was weight, then the data would be quantitative like “125, 155, 223, 178, 222, etc” the data from quantitative variables are numbers

31
Q

what is the difference between discrete and continuous variables?

A

discrete can be counted like “number of cars sold” they are generally integers (you wouldn’t sell 9.3 cars) while continuous would be something like the weight of a mouse

32
Q

what is a quantitative variable?

A

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

33
Q

what is a categorical variable?

A

categorical (qualitative) variables are like categories blonde, listens to hip hop, female, yes, no etc.

34
Q

what do we sometimes call a categorical variable?

A

qualitative

35
Q

what is quantitative data?

A

the actual numbers gathered from each subject 2.11 pounds. 67 beats per minute.

36
Q

what is categorical data

A

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

37
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

38
Q

what is frequency?

A

how often something comes up

39
Q

data or datum

A

datum is singular, data is plural

40
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

41
Q

what is meant by relative frequency?

A

the PERCENT that something comes up (frequency/total)

42
Q

how to fine relative frequency

A

frequency/total

43
Q

what is meant by cumulative frequency?

A

add up the frequencies as you go. 25 pieces of candy. 10 in the first hour 5 in the second 3 in the third 7 in the fourth. 10, 15, 18, 25

44
Q

relative cumulative frequency

A

added up percentages. 25 pieces of candy 10 in first hour 5 in second hour 3 in third 7 in fourth. find cumulative percentages 40%, 60%, 64%, 100%

45
Q

what is the difference between a bar graph and histogram

A

bar graph is for categorical data (bars don’t touch) histograms are for quantitative data (bars touch)

46
Q

mean

A

the average. balancing point of the histogram

47
Q

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

A

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

48
Q

what symbols are used for population mean and sample mean?

A

mu for population mean, x-bar for sample mean

49
Q

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

A

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

50
Q

median

A

the middle at number, it splits area in half (always in the position (n+1)/2)

51
Q

mode

A

the most common or the peaks of histogram

52
Q

when do we use mode most often

A

with categorical variables ex) when describing what the average teenager prefers we say “most” chose. tells number of bumps in a histogram for quantitative data (unimodal, bimodal…)

53
Q

why we don’t always use mean

A

it’s not resilient, impacted by skewness and outliers

54
Q

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

A

it depends if we’re talking about height probably mean, if parental income possibly use the median, if talking about music preferences possibly use the mode

55
Q

clear example of where the mean would change but median wouldn’t

A

amount of money in wallets 1, 2, 2, 5, 5, 8, 8, 9 median 5, mean 5 but if it was randomly instead 1, 2, 2, 5, 5, 8, 8, 9000, the median would still be 5, but the mean would be over 1000.

56
Q

mean median mode position on a skewed left histogram

A

mean median mode

57
Q

mean median mode on skewed right histogram

A

mode median mean

58
Q

who chases the tail?

A

the mean chases the tail, the mean chases the tail, high-ho the derry-oh the mean chases the tail… and outliers…

AP Stats (1 decks)

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