Data Science

Question 1

quantitative data

Answer 1

used to measure the amount of something (eg: mass)

Question 1

categorical data

Answer 1

used to classify instead of measure (eg: species of an animal)

Question 2

Definitions area

Answer 2

where you write the code in Pyret

Question 3

Interactions area

Answer 3

where the output is

Question 4

Pyret decimals

Answer 4

must start with 0.

Question 5

bar chart

Answer 5

count
Visual representation of value’s frequency
Column for every category

Question 6

Pie chart

Answer 6

Percentage
Visual representation of RELATIVE frequency
slice for every column
Max 7 slices, generally 5

Question 7

stacked bar chart

Answer 7

shows more detail about another column (eg: count of species and sex)

Question 8

data cycle

Answer 8

ask questions, consider data, analyze data, interpret data (mnemonic: QCAI )

Question 9

lookup questions

Answer 9

answered by looking up a single value in a table

Question 10

arithmetic questions

Answer 10

computing an answer within a single column Can be finding the average, max, min in a column

Question 11

statistical questions

Answer 11

asks a question about the relationship between two columns?

Question 12

null hypothesis

Answer 12

a type of statistical hypothesis that proposes no statistical significance exists in a set of given observations

Question 13

random samples

Answer 13

a subset of a population in which each member has an equal chance of being chosen. Larger the random sample, the more accurate

Question 14

grouped samples

Answer 14

a subset of the population in which each member of the subset was chosen for a specific reason

Question 15

file extension purpose

Answer 15

tell your computer which application created or can open open the file and which icon to use for the file

Question 16

what does CSV stand for?

Answer 16

comma-separated values

Question 17

histograms

Answer 17

shows the number of rows that fall within certain intervals (or “bins”) along the horizontal axis

Question 18

⬛️⬛️
⬛️⬛️⬛️⬛️

Answer 18

?

Question 19

type of histogram
📉
(imagine this as a histogram)
⬛️
⬛️⬛️
⬛️⬛️⬛️
⬛️⬛️⬛️⬛️⬛️⬛️⬛️

Answer 19

skew right

Question 20

type of histogram
📈
(imagine this as a histogram)
⬛️
⬛️⬛️
⬛️⬛️⬛️
⬛️⬛️⬛️⬛️⬛️⬛️

Answer 20

Skew left

Question 21

what does it mean to be an outlier

Answer 21

Compare it to the other data. But it is important to think about all extreme data points, not just outliers

Question 22

mean

Answer 22

average
symmetric medium-large dataset

Question 23

median

Answer 23

Half the values are smaller and half are larger. The middle number or average of two middle #s
If data is asymmetric, use median

Question 24

mode

Answer 24

or #s that occur the most often in a dataset
in small dataset, mode will likely be most accurate measure of center

Question 25

how many quartiles are in a box plot?

Answer 25

3

Question 26

histogram and box plot shape

Answer 26

whisker direction is the same direction as the skew

Question 27

standard deviation

Answer 27

the most useful way to summarize spread of quantitative columns

Question 28

how to calculate standard deviation

Answer 28

average spread from mean

Question 29

standard deviation equation

Answer 29

sqrt([number of squares of distances] / [# - 1] )

Question 30

explanatory variable

Answer 30

a type of independent variable (x)
scatterplot

Question 31

response variable

Answer 31

a type of dependent variable (y)
scatterplot

Question 32

r

Answer 32

correlation statistic
between -1 and +1
-1 = strongest negative correlation
+1 = strongest positive correlation
0 = no correlation

Question 33

what is the regression line also known as?

Answer 33

Line of best fit, least quares line, predictor, trendline

Question 34

definition of a row

Answer 34

cat-row = row-n(animals-table, #)

Question 35

look up identify

Answer 35

cat-row[species”]
(have cat-row predefined)

Question 36

how to make a function

Answer 36

fun gt(name): fun(parameters) end

Question 37

what is an example for functions?

Answer 37

shows what the function does

Question 38

example example

Answer 38

fun f(x): x / 2 end
examples
f(2) is 2 / 2
f(10) is 10 / 2
end

Question 39

what functions need a helper function

Answer 39

image-scatter-plot, build-column

Question 40

what function to make a specific table

Answer 40

sort or build-column
filter(build-column(animals-table, “kilos”, kilogram), is-heavy)

Question 41

syntax errors

Answer 41

typos and easy to spot. code will not run

Question 42

runtime error

Answer 42

the app runs for a bit and crashes at specific point in the code

Question 43

logic error

Answer 43

the app runs completely but simply produces the wrong input

Question 44

four categories of dirty data

Answer 44

missing data, inconsistent types, inconsistent units/invalid range, inconsistent naming

Question 45

missing data

Answer 45

some cells have data. Some do not

Question 46

inconsistent types

Answer 46

a column where the values have different data types. (eg: 2, two)

Question 47

inconsistent unit/ invalid range

Answer 47

where the data types are the same but represent different units

Question 48

inconsistent naming

Answer 48

inconsistent spelling and capitalization in entries

Question 49

selection bias

Answer 49

if the participants selected are representative of the group study

Question 50

bias in the study design

Answer 50

if the study was not designed specifically and ended up not measuring what was asked very specifically

Question 51

poor choice of summary

Answer 51

using the wrong data analysis technique: mean/median

Question 52

confounding variables

Answer 52

correlation does not imply causation. an outside influence other than the one being studies

Question 53

intentionally using the wrong chart

Answer 53

misleads the audience, can remove holes in data, making it inaccurate

Question 54

changing the scale of a chart

Answer 54

makes the data look a certain way