FIXED UNIT 1 TEST - in order

Question 1

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

Answer 1

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 (aka the parameter of interest).

Question 2

If you are tasting soup.. Then the flavor of each individual thing in the spoon is the _____, the contents of the entire spoon is a ______.. The flavor of all of that stuff together on the spoon is like the _____ and you use that to _____ about the flavor of the entire pot of soup, which would be the__________.

Answer 2

If you are tasting soup. Then the flavor of each individual thing in the spoon is DATA, the contents of the entire spoon is a SAMPLE. The flavor of all of that stuff together on the spoon 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.

Question 3

Which is more sensitive to outliers and skewed? Mean, median. Sd or IQR?

Answer 3

Mean and SD are most influenced by outliers. median and IQR are RESISTANT, RESILIENT, ROBUST!!

Question 4

Can numbers be CATEGORICAL?

Answer 4

sure. Zip codes, sports jersey numbers, telephone numbers, social security nunmbers, area codes… these are categorical.

Question 5

Compare data to parameters

Answer 5

Data is each little bit of information collected from the subjects. They are the INDIVIDUAL little things we collect, like “5, 7, 9” . if we have all of the data from the population, then we can summarize it by finding the average and that would be called a parameter. (if we only had a sample then the summary is called a statistic)

Question 6

Compare DATA-STATISTIC-PARAMETER using CATEGORICAL example

Answer 6

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.” Notice that for categorical variables, the categories are words and the statistics and parameters are percents.

Question 7

Compare DATA-STATISTIC-PARAMETER using QUANTITATIVE example

Answer 7

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”

Question 8

Compare Descriptive and Inferential STATS

Answer 8

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

Question 9

Compare population to sample

Answer 9

populations are generally large, and samples are small subsets of these population. We take samples to make inferences about populations. We use statistics to estimate parameters.

Question 10

data or datum?

Answer 10

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 his brussel sprouts”

Question 11

Does a census make sense?

Answer 11

A census is ok for small populations (like Mr. Nystrom’s students) but impossible if you want to survey “AVERAGE TREE HEIGHT IN THE US”

Question 12

How do you find relative frequency?

Answer 12

PERCENTS- just divide frequency by TOTAL. a percent is relative to the whole.

Question 13

If I take a random sample 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 _______?

Answer 13

statistic. It is a summary of a sample.

Question 14

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 ____?

Answer 14

a datum, or a data value.

Question 15

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 ______?

Answer 15

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

Question 16

If you are calculating a mean, then you must have ______ data

Answer 16

quantitative

Question 17

if you are calculating a percent, then you must have _____ data

Answer 17

categorical

Question 18

Make a guess as to what relative cumulative frequency is…

Answer 18

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 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.

Question 19

Percents are also known as ______

Answer 19

proportions

Question 20

What is the difference betwen a categorical variable and categorical data?

Answer 20

If you wanted the percent of cape cod dogs that are brown, the variable would be “dog color” and the data would be: brown, black, white, mixed, brown

Question 21

What is the is the difference between quantitative data and quantitative variables?

Answer 21

If you want average cape cod dog weight… the variable would be “WEIGHT”– the data are the individual weights.. the actual numbers: 2.3lbs, 5.5 lbs.

Question 22

What is the difference between popluation of interest, variable of interest and parameter of interest?

Answer 22

If we want the average weight of cape cod dogs, population is cape cod dogs, the variable is the weight, the parameter is the mean weight. If we wanted the percent that are brown, the population would still be cape cod dogs, the variable would be dog color and the parameter would be % brown.

Question 23

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?

Answer 23

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 population parameter.

Question 24

What are 2 major branches of AP STATS?

Answer 24

Inferential and Descriptive

Question 25

What are DESCRIPTIVE STATS?

Answer 25

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

Question 26

What are random variables?

Answer 26

ANY QUALITY MEASURED FROM A RANDOMLY CHOSEN SUBJECT. f you randomly choose people from a list, then any quality measured.. their hair color, height, weight can be considered random variables. Same thing with cars.. If you randomly pick them then any quality measured is a random variable.

Question 27

What do we sometimes call a categorical variable?

Answer 27

qualitative

Question 28

What is a categorical variable? Compare to categorical data.

Answer 28

Categorical (or qualitative) variables are the categories you are interested in like "hair color" and "music preference". The data are the measureds from individuals like: SUV, sedan, Listens to Hip Hop, Female, yes, no, etc.

Question 29

What is a census?

Answer 29

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

Question 30

What is a frequency distribution?

Answer 30

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

Question 31

What is a parameter?

Answer 31

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

Question 32

What is a population?

Answer 32

(not necessarily people). the group of stuff you're interested in. It could be "bags of potato chips.." Sometimes it’s big, like "all teenagers in the US" other times it is small, like "all AP Stats students in my school"

Question 33

What is a quantitative variable? Compared to quantitative data?

Answer 33

Quantitative variable are the things your are interested in like: Height, age, price, number of cars sold, SAT score. Quantitative data are the actual heights or ages from individuals: 54" , 2 years, $ 34.99

Question 34

What is a random sample?

Answer 34

When you choose a sample by rolling dice, choosing names from a hat, or other TRULY RANDOM generated sample. Humans can't really do this well without the help of a calculator, cards, dice, or slips of paper.

Question 35

What is categorical data?

Answer 35

The actual individual category from a subject, like "sedan" or "blue" or "female" or "sophomore"

Question 36

What is data?

Answer 36

Any collected information. Generally each little measurement, Like, if it is a survey about liking porridg, 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”

Question 37

What is frequency?

Answer 37

How often something comes up

Question 38

What is INFERENTIAL STATISTICS?

Answer 38

The part of the course where you 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 (the population)

Question 39

What is meant by cumulative frequency?

Answer 39

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

Question 40

What is meant by relative frequency?

Answer 40

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

Question 41

What is quantitative data?

Answer 41

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

Question 42

What is the couse "Statistics" about?

Answer 42

The study of variability. Not just how individual subjects vary, but later on how two different samples from the same population can get different summaries. We later look at how statistics vary from sample to sample.

Question 43

What is the difference between a bar chart and a histogram

Answer 43

bar charts are for categorical data (bars don't touch and can often be in any order) and histograms are for quantitative data (bars usually touch and x axis is in order)

Question 44

What is the difference between a parameter and a statistic?

Answer 44

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

Question 45

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

Answer 45

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.

Question 46

What is the difference between a sample and a census?

Answer 46

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.

Question 47

What is the difference between categorical VARIABLES and categorical DATA?

Answer 47

The Variable is the overall category. Like "EYE COLOR". The data is the actual measurement from the subjects. Like "blue, brown, blue"

Question 48

What is the difference between discrete and continuous variables?

Answer 48

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. Summaries of discreet variables will often be decimals.

Question 49

What is the difference between quantitative and categorical data?

Answer 49

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 simpy "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.

Question 50

What is the difference between quantitative and categorical variables?

Answer 50

Quantitative variables are numerical measures, like height and IQ. Categorical are categories, like eye color and music preference

Question 51

What is variability?

Answer 51

Differences, how things differ. There is variability everywhere. We all look different, act different, have different preference. Statisticians look at these differences. SAMPLE STATISTICS ALSO VARY FROM SAMPLE TO SAMPLE.

Question 52

What parameter do you usually calculate for categorical data?

Answer 52

%, percent, or proportion

Question 53

What parameters do you usually calculate for quantitative data?

Answer 53

mean (and sd) or median (and IQR)

Question 54

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

Answer 54

Mu for population mean, xbar for sample mean.

Question 55

What symbols do we use for population proportion (%) and sample proportion (%)?

Answer 55

p for population and p-hat for sample

Question 56

What symbols do we use for population standard deviation and sample standard deviation?

Answer 56

Sigma for population and s for sample.

Question 57

When can you round?

Answer 57

AT THE VERY END!!! (keep 3 digits until end!)

Question 58

How could you use mode with categorical variables?

Answer 58

With categorical variables. For instance, to describe the average teenagers preference, we often speak of what “most” students chose, which is the mode. "the average teenager likes mexican food." It is also tells the number of bumps in a histogram for quantitative data (unimodal, bimodal, etc…).

Question 59

When drawing a graph or chart, what do you have to remember to do?

Answer 59

LABEL AXES, make a KEY(if needed ) AND GIVE IT A NAME!!! "Figure 1: Age and Food Preference"

Question 60

When we say "the average teenager" are we talking about mean, median or mode?

Answer 60

It 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.

Question 61

You calc percents with ___ data

Answer 61

categorical

Question 62

You calc means/SD with ___ Data

Answer 62

quantitative

Question 63

Who chases the tail?

Answer 63

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

Question 64

Another name for "skewed right" is

Answer 64

positively skewed

Question 65

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

Answer 65

goes in that order, mean median mode (mean chases the tail to balance the histogram)

Question 66

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

Answer 66

mode- median- mean (mean chases the tail)

Question 67

How can you think about the mean, median and mode remember the difference when looking at a histogram?

Answer 67

mean is balancing point of histogram, median splits the area of the histogram in half, mode is the highest point or points

Question 68

If a distribution is skewed left, what will be greater, the mean or median? WHY?

Answer 68

Median. The mean moves left to keep balance.

Question 69

If a distribution is skewed right, what will be greater, the mean or median? WHY?

Answer 69

Mean. The mean moves further to the right to keep balance.

Question 70

If the mean is above the median, the distribution may be

Answer 70

skewed right or positively skewed, the mean follows the tail

Question 71

mean/SD/median/IQR. How do I know which ones to use?

Answer 71

when unimodal and symmetric, mean and sd. If skewed or outliers? Median and IQR. If bimodal? Talk about the MODES

Question 72

what is a clear example of the median's resiliance and when you would use the median instead of the mean?

Answer 72

Imagine the amount of money in peoples pockets: {1, 2, 2, 5, 5, 8, 8, 9}. The mean and median are both 5. You might say "the average person in this group had 5 bucks." But imagine if the 9 was actually 9000 (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. If asked about the average person, would you say 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. When there are outliers or skewed data, use the median.

Question 73

what is a nice mean/median/mode helper diagram?

Answer 73

Sketch a skewed left distribution, then mean/median/mode will be labeled in order from L to R

Question 74

What is the mean?

Answer 74

(a point estimate) the old average we used to calculate. It is the balancing point of the histogram

Question 75

What is the median?

Answer 75

(a point estimate) the middlest number, it splits area in half . Always in the POSITION (n+1)/2

Question 76

What is the mode?

Answer 76

(a point estimate) the peaks of a histogram (the humps). or with categorical data, the most popular category

Question 77

Why don't we just use the average (mean) all the time? (instead of mode and median)

Answer 77

The word average is a general term that can be actually talking about the mean, median or mode. We don't always use the mean because it is not RESILIENT, it is impacted by skewness and outliers

Question 78

What if you accidentally delete L1 in your calculator?

Answer 78

stat>set up editor

Question 79

how do you find summary statistics (mean, st. dev, median, 5 number summ)

Answer 79

stat>calc> 1-VarStats (if frequency table, be sure to do 1-var stats L1, L2)

Question 80

What are the displays you can use for QUANTITATIVE DATA?

Answer 80

stem and leaf, dot plot, historgram, ogive (cumulative frq), box/whisker, normal probability chart

Question 81

What are the displays you can use for CATEGORICAL DATA?

Answer 81

bar chart, pie chart, segmented bar chart,

Question 82

what display could you use to compare two quantitavive data sets?

Answer 82

side by side stem/leaf, histograms or box whiskers, or back to back stem/leaf or histogram, two ogives on same graph,

Question 83

What display would you use to compare two categorical data sets?

Answer 83

side by side segmented bar, mosaic plot, side by side pie charts or bar charts (or one on top of the other)

Question 84

For information purposes, which gives LEAST… stem-leaf, histogram or box-whisker?

Answer 84

Box/Whisker, BE CAREFUL. you really don't know how things are distributed. The box and whisker and fish tank give a very GENERAL look.

Question 85

For information purposes, which gives most… stem-leaf, histogram or box-whisker?

Answer 85

Stem leaf gives the actual values and the shape… histogram just the shape… and box-whisker the least amt, but are great for comparing multiple distributions.

Question 86

How can you match boxplots to histograms?

Answer 86

USE THE FISH TANK METHOD!

Question 87

How do you find Q1 and Q3?

Answer 87

Q1 is the median of the bottom half and Q3 is the median of the upper half (they are the 25th and 75th percentiles)

Question 88

What are the percentiles for Q1, med, and Q3?

Answer 88

25, 50 and 75

Question 89

What is the five number summary?

Answer 89

min, Q1 , Q2(median), Q3 and max

Question 90

What is the IQR?

Answer 90

Interquartile range… a measure of spread. Q3-Q1. The distance from Q1 to Q3. The regular range is Hi-Lo, this is the inner range, the interquartile range.

Question 91

What percent of the data is above Q3?

Answer 91

25%

Question 92

What percent of the data is below the median?

Answer 92

50%

Question 93

What percent of the data is between Q1 and Q3?

Answer 93

50%

Question 94

What percentile is Q1?

Answer 94

25th

Question 95

What percentile is Q3?

Answer 95

75th

Question 96

What percentile is the median (aka Q2)?

Answer 96

50th

Question 97

When are box plots used most often?

Answer 97

When comparing a bunch of different sets of data.

Question 98

where are the "outlier fences?"

Answer 98

1.5 IQR above Q3 and 1.5 IQR below Q1. Just a rule of thumb.

Question 99

How can you describe shape?

Answer 99

unimodal, bimodal, multimodal, uniform, symmetric, skewed

Question 100

How can you describe shape?

Answer 100

TWO THINGS: modes and symmetry. unimodal, bimodal, multimodal AND uniform, symmetric, skewed

Question 101

How can you describe spread?

Answer 101

range, IQR, stand dev, variance, or simply say: From here, to about here

Question 102

How can you describe the center of a distribution?

Answer 102

OPTIONS: give the mean (balance), median (splits area in half), mode (peaks, if bimodal talk about both modes) or say "centered around ____"

Question 103

How do you describe CENTER for bimodal or multimodal?

Answer 103

talk about the modes (the lumps, the clusters)

Question 104

How do you describe CENTER for skewed or distributions with outliers?

Answer 104

use the MEDIAN

Question 105

How do you describe CENTER for unimodal and symetric distributions?

Answer 105

use the MEAN

Question 106

How do you describe distributions (histograms)?

Answer 106

Shape-Cener-Spread- and STRANGE (Outliers and gaps) some say GSOCS. where's yo GSOCS?

Question 107

How do you describe SPREAD for bimodal or multimodal?

Answer 107

talk about the outer edges of the clusters "from here to here" or use the IQR.

Question 108

How do you describe SPREAD for skewed distributions (or distributions with outliers?)

Answer 108

Use the IQR

Question 109

How do you descrive SPREAD for unimodal and symmetric distributions?

Answer 109

use the standard deviation

Question 110

If asked to compare distributions, what should you write about?

Answer 110

A sentence comparing the SHAPES. A sentence comparing the CENTERS. A center comparing the SPREADS. and a sentence comparing the STRANGE STUFF. (GSOCS)

Question 111

If the distribution is bimodal or multimodal, what would you use for center and spread statistics?

Answer 111

Talk about each mode (center) and maybe use the range or IQR. You could also say "one group seems to go from __ to __ and the other from about __ to __"

Question 112

If the distribution is skewed (or outliers/not symmetric) what would you use for center and spread statistics?

Answer 112

Median (center) and IQR (spread)

Question 113

If the distribution is unimodal and symmetric, what would you use for center and spread statistics?

Answer 113

Mean (center) and Standard Deviation (spread)

Question 114

What does GSOCS stand for?

Answer 114

Gaps Shape Outliers Center Spread. I usually say "shape, center, spread, strange" SCSS

Question 115

How can you turn OGIVES into histograms?

Answer 115

RECTANGLE DROP! (bin drop)

Question 116

How do you find 5 number summary from OGIVE?

Answer 116

Split the y axis in half, then half the top and bottom (making quarters). Shoot out to the right from 0, .25, .50, .75 and 1.00 till you hit the ogive, then go straignt down. Those numbers on the x axis correspond to the 5 numbers.

Question 117

How do you find 5 number summary from OGIVE?

Answer 117

Split the y axis into quarters. Shoot out to the right from 0, .25, .50, .75 and 1.00 till you hit the line in the ogive, then go straignt down. Those numbers on the x axis below correspond to the 5 numbers.

Question 118

How do you find a certain percentile on an OGIVE?

Answer 118

Start at the % on the x axis.. travel horizontally to the right until you hit the line, then straight down. That data value is the percentile.

Question 119

How do you find percentiles and make a boxplot from OGIVE?

Answer 119

Go across till you hit the curve and then STRAIGHT DOWN!

Question 120

How do you find the median fro man OGIVE?

Answer 120

go halfway up the y axis, then shoot across to the curve, then straight down. It's at the 50th percentile (halfway up)

Question 121

How do you match OGIVES to histograms?

Answer 121

RECTANGLE DROP!!

Question 122

What do OGIVES look like?

Answer 122

They all start at the bottom left (0%) and go to top right (100%)

Question 123

What is a CUMULATIVE FREQUENCY GRAPH?

Answer 123

An OGIVE. It shows the added up totals as you go left to right.

Question 124

are any populations actually normal?

Answer 124

no, nothing is normal, just normalish. The only normal thing is the model we use.

Question 125

are there any normal samples?

Answer 125

no, nothing is normal, just normalish. The only normal thing is the model we use.

Question 126

Does the IQR capture 68% of the data?

Answer 126

NO. it catches the middle 50%.

Question 127

How do students often mix up IQR and St. Dev

Answer 127

They INCORRECTLY think that Q1 is 1sd below the mean and Q3 is 1sd above the mean. THIS IS NOT TRUE!!! Q1 is only .67 sd above the mean and Q2 is .67 below

Question 128

How many SD wide is the IQR in a normal distribution?

Answer 128

NOT 2!!!! Think about it. The middle 68% is 2 sd wide, since the IQR is only the middlest 50% it must be less than 2. try [invnorm(.75)] x2. You find that it is only 1.35 SD wide if the distribution is nearly normal.

Question 129

If you want to calculate % above a value, what do you put into normcdf(? ?)

Answer 129

find z score for value, and then normcdf (Z left, 999)

Question 130

If you want to calculate the probability (%) something falls between two values in a normal model, what do you do?

Answer 130

find z scores for both value, and then normcdf (Z LOW, Z HIGH )

Question 131

If you want to find % below a value, what do put into normcdf (? ?)

Answer 131

find z score for value, and then normcdf (-999, Zright)

Question 132

If you want to find percentile for a value, what do you put into normcdf (? ?)

Answer 132

find z score for value, and then normcdf (-999, Zright) like going from negative infinity up to the z score

Question 133

If you want to find the value that is in the top 7 percent, what do you do?

Answer 133

use INVNORM(.93)

Question 134

the output for normcdf(Zleft, Zright) is_______

Answer 134

the area under the normal curve between the given z scores

Question 135

what are the percentiles from left to R on normal model?

Answer 135

2.5-16-50-84-97.5

Question 136

What does invnorm do?

Answer 136

it gives you the z score from a percentile

Question 137

What does normcdf do?

Answer 137

It gives you the area under the normal curve between any two z scores

Question 138

What is a "percentile?"

Answer 138

It tells you the percent of data BELOW a certain value

Question 139

What is a standard deviation?

Answer 139

average (typical) distance to the mean (about). It is how far you expect a random value to be away from the middle.

Question 140

What is a statistic?

Answer 140

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

Question 141

What is a Z score?

Answer 141

The number of standard deviaiton away from the mean

Question 142

what is the emperical rule?

Answer 142

mean 68-95-99.7 yeah!

Question 143

what is the shortcut invnorm?

Answer 143

gives data value from percentile, skips Z score. Invnorm (percentile, mean, sd)

Question 144

what is the shortcut normcdf?

Answer 144

gives % from raw data, skips Z score. normcdf (low VALUE, high VALUE, mean, sd)

Question 145

What is the total area under the normal curve?

Answer 145

1 or 1.000

Question 146

What is the total area under the normal curve?

Answer 146

1 or 1.000 (or 100%)

Question 147

What is the variance?

Answer 147

The average squared distance to the mean. Or the SD2 (It is the SD before you take the square root, so it is the stuff under the radical in the formula)

Question 148

When drawing a normal model, what are the PERCENTILES from left to right?

Answer 148

2.5, 16, 50, 84, 97.5

Question 149

which calculator function gives you a percent?

Answer 149

normcdf(Z left, Z right)

Question 150

Which calculator function gives you a z score?

Answer 150

invnorm(%ile)

Question 151

Why are there different standard deviation formulas for population and sample? Arent they the same thing?

Answer 151

Both equations are actually doing the same thing. They both attempt to calculate the true population proportion. When you have all of the data from the population you just divide by n and get the actual SD. BUT If you only have a sample then you are using that to make a guess (inference) at what the population standard deviation is.. What happens is that samples tend to have less spread so their SD underestimates the population, BUT, when you divide by n-1 instead of n, It gives you a better estimate of what the population standard deviation is.

Question 152

Why do we plug 999 into normcdf?

Answer 152

It needs a z score, but we can't plug in infinity. So we go down or up 999 standard deviations and that pretty much gets everything

Question 153

associated is the same as __________

Answer 153

not independent

Question 154

Association and Independence. How are they related?

Answer 154

Variables are either independent or associated. Meaning: if one impacts the other then we say there is an association. If not, Then they are independent.

Question 155

conditional distribution?

Answer 155

A distribution within the table, along only one row or one column… NOT IN THE MARGINS. You are given a condition.. Then read along that row or column.

Question 156

Gender and Video Game playing are___________ because_______

Answer 156

associated (or not independent) because a higher percentage of males play video games. (think.. It depends on gender)

Question 157

Give a quick example of associated variables

Answer 157

A higher percentage of boys play video games than girls so we say "gender and video game playing are associated" or "gender and video game playing are not independent"

Question 158

Give an example of independent variables

Answer 158

If 80% prefer cheese and only 20% prefer pepperoni IN EACH GRADE AT BHS…then they all have the same preference, so grade doesn't matter. We say "school year and pizza choice are independent"

Question 159

How can you tell if variables in a contingency table are independent?

Answer 159

If the distributions are the same across the variables.. Then it doesn't DEPEND… so INDEPENDENT. Ex: 30% of freshman and 30% of seniors like cabbage.

Question 160

independent is the same as __________

Answer 160

not associated

Question 161

marginal distribution

Answer 161

distribution in the margins (outside of the table). The overall distributions of a single variable in contingency table.

Question 162

not associated is the same as being ____________

Answer 162

independent

Question 163

not independent is the same as being ____________

Answer 163

associated

Question 164

What do you call things that are not independent?

Answer 164

associated. Or not independent. We generally don't say DEPENDENT (unless talking about y variable on a scatterplot).

Question 165

what is a conditional distribution?

Answer 165

A distribution with a condition (within the table), along only one row or one column… NOT IN THE MARGINS. You are given a condition.. Then read along that row or column.

Question 166

What is a contingency table?

Answer 166

shows distributions across 2 variables like gender and music pref. AKA 2-way table

Question 167

When there is a relationship between two variables, we say that they are

Answer 167

associated (or not independent)

Question 168

When there is no relationship between two variables, we say they are

Answer 168

independent (or not associated)

Question 169

Year in school (F,S,J,S) and Pizza Preference (pepperoni or cheese) are __________ because _______________

Answer 169

independent because all grades have similar preference distributions.. 40% cheese, 30%pepperoni, 20% veggie 10% other

Question 170

Give a simple example showing that adding a constant doesn't change the spread, but changes the center. (this always happens)

Answer 170

Data set: 1,2,3,4,5 Spread (range):4, Center: 3 add three and get new data set: 3,4,5,6,7 spread:4 Center: 5 (center went up, spread stayed the same). The IQR and SD will stay the same, but median and mean go up 3. Called shifting, or sliding the data.

Question 171

How does multiplying by a constant impact the summary statistics of a data set? (or random variable)

Answer 171

It is SCALED. Both center and spread are effected. They all (mean, median, IQR, SD, range) get multiplied by three. (BE CAREFUL, remember the variance is the SD squared, so the variance gets multiplied by 9).

Question 172

Think of the minimum value, the mean and the standard deviation, what is impacted by adding a constant (shifting)?

Answer 172

adding a value shifts the entire histogram to the right, so the min and the mean will increase by that amount, BUT THE SD WILL NOT CHANGE.

Question 173

Think of the minimum value, the mean and the standard deviation, what is impacted by multiplying all data in the set by a constant (scaling)?

Answer 173

If you multiply a data set by a number, then the min, mean and the SD will multiply by that number.

Question 174

What does SHIFT and SCALE mean?

Answer 174

Shift is when you add or subtract (it slides the histogram left and right), scale is when you multiply

Question 175

what happens if you ADD a constant to each value in a data set?

Answer 175

it is SHIFTED only. Does not impact spread. This effects all of the data values and measures of center (mean, med) and quartiles, deciles, etc, IT DOES NOT CHANGE THE SPREAD! (IQR, St Dev, Range all stay the SAME).

Question 176

what happens if you multiply all of a data set by a constant? Think of an example

Answer 176

it is scaled Both center and spread are impacted. Mean/ median/ stand dev/ iqr/ quartiles all multiplied by that constant. Center, spread and all individual values are changed. Consider 1,2,3,4,5 mean of 3 and range of 4. Now multiply by 3: 3,6,9,12,15 and you get a mean of 9 and a range of 12... both multiplied by three.