intro to data

Question 1

data matrix

Answer 1

table of data
columns : variables
rows : individuals

Question 2

what are variables and individuals
(information given in data)

Answer 2

variables = characteristics
individuals = observational unit

Question 3

quantitative variablee

Answer 3

numerical or measurement variable
ex: age, distance
two types: discrete & continuous

Question 4

quantitative variable
discrete

Answer 4

can only take numerical values with jumps,
1, 2, 3, 4
# of plants in a garden # of dogs in a house

Question 5

quantitative variable
continuous

Answer 5

can take on any value in an interval
temperature throughout the day
decimals

Question 6

categorical variable

Answer 6

qualitative variable
place an individual or item into one of several groups or categories called levels

Question 7

examples of levels

Answer 7

blood types (A,B, AB, O)
gender

Question 8

two types of categorical variables

Answer 8

nominal and ordinal

Question 9

categorical variable
nominal

Answer 9

no natural ordering for the categories
Ex: dog breed, brand of soda

Question 10

categorical variable
ordinal

Answer 10

have a logical order for categories
ex: size of soda, grade level

Question 11

what graphs are used to graph categorical data

Answer 11

bar graph and pie chart

Question 12

box plot qualities

Answer 12

shows the median using dark horizontal line
can’t see the number of modes

Question 13

what graphs are used to graph quantitative data

Answer 13

dotplots and histograms

Question 14

dotplots qualities

Answer 14

represents each observation in a data set using a single dot along the x-axis
do well displaying values of a variable in a smaller data set
NOT good at displaying data with too many different values —> lose sense of overall distribution

Question 15

histograms qualities

Answer 15

give a good sense of the shape of the distribution
shows the modes
symmetry is visible

Question 16

distribution

Answer 16

what values does the variable take and how often

Question 17

modes

Answer 17

of peaks
univocal, bimodal, multimodal

Question 18

symmetry

Answer 18

symmetric
skewed to right (tail on right) lower values
skewed to left (tail on left) higher values

Question 19

outliers

Answer 19

observations that lie outside the overall pattern of distribution
^^ must consider reason they exist

Question 20

population

Answer 20

the entire group we are interested in learning about

Question 21

sample

Answer 21

subset of individuals that is often a small fraction of the overall population

Question 22

parameter

Answer 22

the numerical summary for a characteristic of the population (as a whole)
keyword : “All”

Question 23

statistic

Answer 23

the numerical summary for a characteristic of a sample
keyword: sample

Question 24

what two goes together
sample and parameter
statistic and population

Answer 24

sample is a statistic
population is a parameter

Question 25

sample mean

Answer 25

the sum of the observations divided by the # of observations
symbol: x bar
center when distribution is roughly symmetric

Question 26

sample median

Answer 26

the middle value when data are arranged from smallest to largest
center when distribution is skewed

Question 27

mean and median sensitivity to extremes

Answer 27

mean = sensitive to extremes
median = resistant to extremes

Question 28

what does the mean and median value relative to each other, tell us about the distribution
mean= median
mean>median
mean<median

Answer 28

mean = median : approximately symmetric
mean>median : skewed to right
mean<median : skewed to left

Question 29

range

Answer 29

maximum- minimum
very sensitive to extremes

Question 30

interquartile range

Answer 30

goes hand in hand with median
used to measure variability when median is the center
IQR = Q3-Q1
describes the variability of the middle 50% of data
NOT sensitive to extreme values

Question 31

percentiles

Answer 31

first percentile Q1 the 25th percentile
third percentile 75th percentile Q3

Question 32

standard deviation

Answer 32

used as measure of variability when sample mean is the measure of center
tells us how much an observation departs from the mean :observation - mean

Question 33

sample variance

Answer 33

s^2 = sum of squared deviations / n-1

n = number of observations

Question 34

sample standard deviation equation

Answer 34

s = sqrt (all observations - means)^2 / n-1

Question 35

how do u know if there is more variability when you look at standard deviation value (s)

Answer 35

when s is larger

Question 36

what two descriptions go together and when
median
mean
iqr
standard deviation

Answer 36

median and iqr = skewed
mean and sd = symmetric

Question 37

how to describe distribution of a graph

Answer 37

SOCS
shape - (# of modes/ symmetric? skewed?)
Outliers (do they exist?)
center (mean or median)
spread/variability (IQR or SD)

Question 38

suspected outliers in boxplots

Answer 38

points that lie at or below Q1-1.5xIQR or at or above Q3+1.5xIQR