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AP stat vocab > test 1 > Flashcards

test 1 Flashcards

1
Q

Statistics

A

Study of variability

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2
Q

Variability

A

All things have differences, and statisticians look a these differences

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3
Q

2 branchs of AP stats

A

inferential and descriptive

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4
Q

descriptive stats

A

describe collected data using pictures or summaries like mean, median, range, etc…

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5
Q

inferential stats

A

look at data of sample and use it to tell about the population

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6
Q

compare descriptive and inferential stats

A

descriptive explains about data; inferential uses data of sample to tell about an entire population

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7
Q

data

A

any collected info., generally each little measurement

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8
Q

population

A

group of interest, can be big or small

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9
Q

sample

A

A subset of population, taken to make inferences about the population, calculate statistics from samples

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10
Q

compare population to sample

A

populations generally are large, samples are small subsets of population; take samples to make inferences about populations, use statistics to estimate parameters

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11
Q

compare data to statistics

A

data is the individual bits of info collected, summarize data by, ex. finding mean of a group of data,
mean of sample is statistic, if data is from each member of population, mean is parameter

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12
Q

compare data to parameters

A

data is the individual bits of collected info, summarize data by, ex. finding mean of a group of data,
mean of sample is statistic, summary of sample; if data is from each member of population, mean is parameter, summary of population

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13
Q

parameter

A

numerical summary of a population like mean, median, mode

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14
Q

stastistic

A

numerical summary of a sample like mean, median, mode

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15
Q

Curious about average wait time at Dunkin Donuts drive through: randomly sample cars and find the average wait time is 3.2 minutes. What is the population parameter, statistic, parameter of interest, data?

A

parameter is the true average wait time at that Dunkin Donuts, a number you don’t have and will never know. Statistic is 3.2 minutes, average of data collected. Parameter of interest= population parameter. Data is the wait time of each individual car, like “3.8 min, 2.2 min, 0.8 min.” Average of that data is statistic, and use that to make inference about the true parameter

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16
Q

Compare DATA-STATISTIC-PARAMETER using categorical example

A

words, put into groups, data are individual measures, statistics and parameters are summaries;

“taco, taco, pasta, taco, burger, burger, taco…” statistic: 42% of sample preferred tacos, and parameter: 42% of population preferred tacos

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17
Q

Compare DATA-STATISTIC-PARAMETER using quantitative example

A

numbers,

“45 sec, 64 sec, 32 sec, 68 sec,” raw data, statistic: average breath holding time in the sample was 52.4 sec, and parameter: average breath holding time in population was 52.4 sec

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18
Q

census

A

sample of entire population, info. from every member of population

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19
Q

does a census make sense?

A

census is ok for small populations, impossible for big populations

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20
Q

difference between a parameter and a statistic

A

both are number summarizing a larger gorup of numbers, parameter from population, statistic from sample

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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 each of them… and one of them had 9 pickles, then the number 9 from that burger would be called?

A

a datum, or a 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 each 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 and count the number of pickles on each of them… and i want to know the true average number of pickles on a burger, which is considered?

A

parameter, a one number summary of the population (parameter of interest)

24
Q

difference between a sample and a census

A

sample, info. from a small part of population; census, info. from entire population; parameter from a census, statistic from a sample

25
Q

population, parameter, census, sample data, statistics, inference, parameter of interest

A

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

26
Q

If you are tasting soup…

A

If you are tasting soup… then the flavor of each individual thing in the spoon is DATA, the entire spoon is a SAMPLE. The flavor of all stuff together is like the STATISTIC, and you use that to MAKE AN 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

random variables

A

randomly choosing people from a list; hair color, height, weight and any other data collected from them can be considered random varaibles

28
Q

difference between quantitative and categorical variables

A

quantitative variables, numerical measures; categorical, categories in words

29
Q

difference between quantitative and categorical data

A

data from quantitative variables are numbers, data from categorical variables are words

30
Q

difference between discrete and continuous variables

A

discrete can be counted and are integers, continuous would have to be measured specifically for, have decimals

31
Q

quantitative variable

A

quantitative variables are numeric

32
Q

categorical variable

A

categories

33
Q

another name for categorical variable

A

qualitative

34
Q

quantitative data

A

actual numbers gathered from each subject

35
Q

categorical data

A

actual individual category from a subject

36
Q

random sample

A

choosing a real randomly generated sample

37
Q

frequency

A

how often something comes up

38
Q

data or datum

A

datum singular, data plural

39
Q

frequency distribution

A

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

40
Q

relative frequency

A

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

41
Q

how to find relative frequency

A

divide frequency by TOTAL

42
Q

cumulative frequency

A

add up the frequencies as you go;

ex. selling 25 pieces of candy, sell 10 the first hour, 5 the second, 3 the third and 7 in the last, the cumulative frequency would be 10, 15, 18, 25

43
Q

relative cumulative frequency

A

add up percentages, take cumulative frequencies and divide by the total giving cumulative percentages

ex. 10/25=0.4, 15/25=0.6, 18/25=0.64, 25/25=1.0; relative cumulative frequencies always end at 100%

44
Q

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

mean

A

average; balancing point of the histogram

46
Q

difference between a population mean and a sample mean

A

population mean=parameter, sample mean=statistic

47
Q

symbols for population mean and sample mean

A

μ for population mean, x̄ for sample mean

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

median

A

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

50
Q

mode

A

the most common, peaks of a histogram, often use mode with categorical data

51
Q

when do we often use mode

A

with categorical variables, describe the average preference, speak of what “most” chose; mode also tells the number of bumps in a histogram for quantitative data (unimodal, bimodal, etc…)

52
Q

why don’t we always use mean

A

it is not RESILIENT, can be impacted by skewness and outliers

53
Q

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

A

depends:
height, mean
parental income, median
music preference, mode

54
Q

clear example of where the mean would change but median wouldn’t? (show its resilience)

A

eight people with money (1, 2, 2, 5, 5, 8, 8, 9), mean and median is 5

if one has big bucks (1, 2, 2, 5, 5, 8, 8, 9000) median still 5, mean goes over 1000; here, 5 is a better description of the average person in this group and 9000 is an outlier

55
Q

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

A

goes in order from left to right, mean-median-mode

56
Q

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

A

goes in opposite order, mode-median-mean

57
Q

who chases the tail

A

the mean chases the tail and outliers

AP stat vocab (1 decks)

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