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Ap stat > Vocab 1 > Flashcards

Vocab 1 Flashcards

1
Q

What is statistics?

A

The study of variability.

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2
Q

What is variability?

A

How things differ from each other.

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3
Q

What are the 2 branches of AP STATS ?

A

Inferential and descriptive.

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4
Q

What are inferential stats?

A

Look at your data and use that to say stuff about the big picture.

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5
Q

What are descriptive stat?

A

Describing the data you collected using pictures summary like mean median range etc.

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6
Q

Compare descriptive and inferential stat

A

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

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7
Q

What is data?

A

Any collected information. Generally each little measurement like a survey.

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8
Q

What is a population?

A

The group you’re interested in. Sometimes it’s big like all teenagers in the US other times it is small like all AP Stat students in my school

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9
Q

What is a sample

A

Subset of a population often taken to make inferences about the population

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10
Q

Compare population to sample

A

Population are generally large and samples are subset of these population. 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 subject. The mean of a sample is called statistic. The mean of the population is called the parameter.

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12
Q

What is statistic

A

A numerical summary of a sample

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13
Q

What is a parameter

A

Numerical summary of a sample

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14
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 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 find the average, that average is called a “statistic,’ and you use that to make an inference about the true parameter.

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15
Q

Compare DATA-STATISTIC- PARAMETER using categorical example

A

Data are individual measures… like meal preference: “taco, taco, pasta, taco, burger, burger, taco”..A Statistics and Parameters are summaries, A statistic would be “42% of sample preferred tacos” and a parameter would be “42% of population preferred taco.

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16
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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17
Q

Does a census make sense?

A

A census is ok for small populations (like Mr. Nystrom’s students) but impossible if you want to survey all US teens.

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18
Q

What is the difference between a parameter and a statistic?

A

BOTH ARE A SINGLE NUMBER SUMMARIZING A LARGER GROUP OF NUMBERS…. But pppp parameters come from pppp populations… sss statistics come from ssss sample.

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19
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, then the number 9 from that burger would be called ?

A

A datum or a data value.

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20
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, then 9.5
is considered a ?
A

Statistic ( it is the summary of a 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 a
bunch of them... and l 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 ?
A

Parameter, one number summary of the population. The truth. AKA the parameter of interest.

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22
Q

What is the difference between a sample and a census?

A

census is you get info from the entire population. You can get a parameter from a census, but only a statistic from a sample.

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23
Q

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

A

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

24
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
of 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 soup Then the flavor of each individual thing in the spoon is
DATA, the entire spoon is a SAMPLE. The flavor of all of that 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.

25
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.

26
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.

27
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 “123, 155, 223, 178, 222, etc..” The data from quantitative variables are numbers.

28
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 weight of a mouse… 4.341102.

29
Q

What is a quantitative variable?

A

Quantitative variables are numeric like: Height, age, number of cars sold, SAT
score.

30
Q

What is a categorical variable?

A

Qualitative variables are like categories: Blonde, Listens to Hip Hop, Female, yes, no… etc

31
Q

What do we sometimes call a categorical variable?

A

Qualitative.

32
Q

What is quantitative data?

A

The actual numbers gathered from each subject. 211 pounds. 67 beats per

33
Q

What is categorical data?

A

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

34
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 well in this without the help of a calculator, cards, dice, or slips of paper.

35
Q

What is frequency?

A

How often something comes up.

36
Q

Data or datum?

A

Datum is singular.. Like “hey dude, come see this datum l got from this rat!” Data is the plural.. “hey look at all that data Edgar got from those chipmunks over there”

37
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.

38
Q

What is meant by relative frequency?

A

The PERCENT of time something comes up (frequency/total)

39
Q

How do you find relative frequency?

A

Just divide frequency by TOTAL…

40
Q

What is meant by cumulative frequency?

A

ADD up the frequencies as you go. Suppose you are selling 25 pieces of candy. You sell 10 the first hour, 5 the second, 3 the third and 7 in the last hour, the cumulative frequency would be 10, 15, 18, 25.

41
Q

Make a guess to what relative cumulative frequency is

A

lt is the ADDED up PERCENTAGES.. An example is selling candy, 25 pieces sold overall,.., with 10 the first hour, 5 the second, 3 the third, and 7 the fourth hour, we’d take the cumulative frequencies, 10, 15, 18 and 25 and divide by the total giving cumulative percentages… .40, .60, .64, and 1.00. Relative cumulative frequencies always end at 100 percent.

42
Q

What is the difference between bar charts and histogram?

A 
bar charts are for categorical data (bars don't touch) and histograms are for
quantitative data (bars touch)
43
Q

What is the mean?

A

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

44
Q

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

A

population mean is the mean of a population, it is 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.

45
Q

What symbols are used for population mean and sample mean?

A

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

46
Q

How can you think about the mean and the median to remember the difference by looking at a histogram?

A

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

47
Q

What is median?

A

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

48
Q

What is mode?

A

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

49
Q

When the most common, or the peaks of a histogram, We often use mode with
categorical data 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. lt is also tells the number of bumps in a histogram for quantitative data (unimodal, bimodal, etc…).

50
Q

Why don’t we always use mean, we’ve been calculating it all our lives?

A

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

51
Q

When it is not RESILIENT, it is impacted by skewness and outliers
we say “the average teenagers” are we talking about mean median or mode?

A

lt depends, if we are talking height, it might be the mean, if we are talking about parental income, we’d probably use the median, if we were talking about music preference, we’d probably use the mode to talk about the average teenager

52
Q

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

A

imagine if we asked eight people how much money they had in their wallet. We found they had {1, 2, Z, 5, 5, 8, 8, 9}. The mean of this set is 5, and the median is also 5. You might say “the average person in this group had 5 bucks.” But imagine if one of them just got back from the casino, and instead it was (1, 2, 2, 5, 5, 8, 8, 9000}, in this case, the median would still be 5, but the mean goes up to over
1000. Which number better describes the amount of money the average person in the group carries, 5 bucks or 1000 bucks? l think 5 is a better description of the average person in this group and the 9000 is simply an outlier.

53
Q

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

A

goes in that order from left to right. Mean-median-mode

54
Q

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

A

goes in the opposite order.. Mode-median-mean

55
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 stat (1 decks)

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