Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

... > Ap Stats Summer Flashcards > Flashcards

Ap Stats Summer Flashcards

1
Q

What is Statistics

A

The study of variability

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What are 2 branches of AP STATS

A

Inferential and Descriptive

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What are DESCRIPTIVE STATS

A

Describe the data that was collected, uses pictures or summaries like mean, median, range, etc..

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What are INFERENTIAL STATS

A

Use data 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)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Compare Descriptive and Inferential STATS

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is data

A

Any collected information. Generally each little measurement … Like, if it is 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”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What is population

A

the group you are interested in. Sometimes its big like “all the teenagers in the US” other times it is small like “ all the AP Stats students in my school”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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 the data. If it is a sample, then we call that mean a “statistic” if we have data from each member of population, then that mean is called “parameter”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Compare data to parameters

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 the data. If it is a sample, then we call that mean a “statistic” if we have data from each member of population, then that mean is called “parameter”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is a parameter

A

A numerical summary of a population. Like a mean, median, range… of a population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is a statistic

A

A numerical summary of a sample. Like a mean, median, range… of a sample

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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 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.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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% of sample preferred tacos” and a parameter would be “42% of population preferred tacos.”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Compare DATA-STATISTIC-PARAMETER using quantitative example

A

Data are individual measures, like how long a person can hold their breath: “45 sec, 64 sec, 32 sec, 68 sec.” 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”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

What is a census

A

Like a sample of the entire population, you get information from every member of the population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Does a census make sense

A

A census is ok for small populations (like Mr. Nystroms students) but impossible if you want to survey “all US Teens”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

What is the difference between a parameter and a statistic

A

Both of a single number summarizing a larger group of numbers… But Parameters come from Population… Statistics come from Samples.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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, then the number 9 from that burger would be called ___?

A

a datum or a data value

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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, then 9.5 is considered a ___?

A

statistic (it is a summary of a sample)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
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 ___?

A

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

24
Q

What is the difference between 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 a population parameter, but the 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 (AKA the parameter of interest).

26
Q

If you are tasting soup.. then the flavor of each individual thing in th 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 th spoon is the 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. 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

29
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, bbrown, brown, blue, green, blue, brown…etc.” The data from categorical variable are usually words, often it is simply “YES, YES, YES, NO, YES, NO” If it was weight, then that data would be quantitative like “125, 155, 223, 178, 222, etc..” The 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 sold” they are generally integers (you wouldn’t sell 9.3 cars), while continuous would be something like weight of a mouse… 4.344 oz.

31
Q

What is a quantitative variable

A

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

32
Q

What is a categorical variable

A

qualitative variables are like categories: Blond, 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 “sophmore”

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.. like “hey dude, come see this datum I got from this rat!” data is the plural..”hey look at all that data Edgar got from those chipmunks over there!”

39
Q

What is 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 times something comes up (frequency/total)

41
Q

How do you find relative frequency

A

just divide frequency by TOTAL…

42
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 the last hour, the cumulative frequency would be 10, 15, 18, 25

43
Q

Make a guess as to what relative cumulative frequency is

A

It 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, we’d take the cumulative frequencies, 10, 15, 18, 25, and divide by the total giving cumulative percentages… .40, .60, .64, 1.00. Relative cumulative frequencies always end at 100 percent

44
Q

What is the difference between a bar chart and a histogram

A

bar charts are the 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 population mean and 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.

47
Q

What symbols do we use for population mean and sample mean

A

Mu (μ) for population mean (parameter), x-bar (x̄) 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)/2 )

50
Q

What is the mode

A

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

51
Q

When do we often use mode

A

With categorical variable. 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, etc…).

52
Q

Why don’t we always use the 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 height, it might be like 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.

54
Q

What is a clear example of where the 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 {1,2,2,5,5,8,8,9} 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 sacino, and instead it was {1,2,2,5,5,8,8,9000} in this case, the median would still be 5, the 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? I think 5 is a better description of the average person in this group and the 9000 is simply an outlier.

55
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

56
Q

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

A

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

57
Q

Who chases the tail

A

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

... (1 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions