study deck 2

Question 1

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 1

a datum, or a data value.

Question 2

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 2

statistic. (it is a summary of a sample.)

Question 3

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 3

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

Question 4

What is the difference between a sample and a census?

Answer 4

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 5

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

Answer 5

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 6

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 .

Answer 6

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. Notice you are interested in the parameter to begin with… that is why you took a sample.

Question 7

What are random variables?

Answer 7

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.

Question 8

What is the difference between quantitative and categorical variables?

Answer 8

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

Question 9

What is the difference between quantitative and categorical data?

Answer 9

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.

Question 10

What is the difference between discrete and continuous variables?

Answer 10

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.

Question 11

What is a quantitative variable?

Answer 11

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

Question 12

What is a categorical variable?

Answer 12

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

Question 13

What do we sometimes call a categorical variable?

Answer 13

qualitative

Question 14

What is quantitative data?

Answer 14

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

Question 15

What is categorical data?

Answer 15

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

Question 16

What is a random sample?

Answer 16

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.

Question 17

What is frequency?

Answer 17

How often something comes up

Question 18

data or datum?

Answer 18

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!!”

Question 19

What is a frequency distribution?

Answer 19

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

Question 20

What is meant by relative frequency?

Answer 20

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

Question 21

How do you find relative frequency?

Answer 21

just divide frequency by TOTAL….

Question 22

What is meant by cumulative frequency?

Answer 22

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 23

Make a guess as to what relative cumulative frequency is…

Answer 23

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 24

What is the difference between a bar chart and a histogram?

Answer 24

bar charts are for categorical data (bars don’t touch) and histograms are for quantitative data (bars touch)

Question 25

What is the mean?

Answer 25

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

Question 26

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

Answer 26

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 27

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

Answer 27

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

Question 28

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

Answer 28

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

Question 29

What is the median?

Answer 29

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

Question 30

What is the mode?

Answer 30

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

Question 31

When do we often use mode?

Answer 31

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

Question 32

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

Answer 32

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

Question 33

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

Answer 33

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

Question 34

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

Answer 34

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 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? I think 5 is a better description of the average person in this group and the 9000 is simply an outlier.

Question 35

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

Answer 35

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

Question 36

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

Answer 36

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

Question 37

Who chases the tail?

Answer 37

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