Data Analytics

Question 1

What is the operator to assign objects to variables

Answer 1

<-
“assign operator”
helps assign objects to variables

Question 2

c() function - what is it?

Answer 2

concatenate - Define a vector

Question 3

tidy or untidy dataframe?

Answer 3

• each variable should have one column; not more

Question 4

What is the pipe operator?

Answer 4

%>% - pipe operators allows to concatenate code so it is more readable; instead of using nested functions; takes whatever comes before the concatenator and sends it to the first argument after; allows to pass code of one function directly into the next function as an argument

Question 5

What function to use for making a dataframe tidy?

Answer 5

pivot_longer()
–> is used to transform data from a wide format (where ecah level of variable has its own column) into a long format (where all values of a variable are placed into a single column)

Question 6

What does group_by() do?

Answer 6

The group_by() function in dplyr is used to group a data frame by one or more variables (columns), so that subsequent operations like summarizing, mutating, or filtering are applied to each group independently

Question 7

What does summarise() do?

Answer 7

the summarise() function in dplyr is used to reduce or summarize a data frame by calculating a single value for each group of data - it is typically used after group_by() to perform aggregate calculations like finding the mean, sum, count, etc.

Question 8

What does mutate() do?

Answer 8

A function which “mutates”, i.e. adds information - compute transformations on columns: create new columns using existing columns - To drop all non-transformed variables use transmute()

Question 9

Confidence interval formula

Answer 9

• x bar +/- z * s/(n^1/2)
• (n = sample size, s = SD of sample)

Question 10

What is the interpretation of the Confidence Interval?

Answer 10

For 95% of the time I am calculating xyz, it is going to fall into that specific interval - 95% of the time the x bar is going to fall into this interval

Question 11

Parameter of the t-distribution

Answer 11

n-1

Question 12

Hypothesis testing - z-test - formula

Answer 12

z-test = | (x bar - mu) / (sigma / n^1/2) |

Question 13

The two outcomes for a hypothesis test

Answer 13

z-test is < (?) than z-critical
–> Fail to Reject the Null Hypothesis / Reject the Null Hypothesis

–> Failing to reject H0 is not the same as accepting H0 - it simply means there isn’t strong enough evidence against H0, not that H0 is true

Question 14

hypothesis testing - comparing to samples - t-test (technically can also be a t-test) - to test whether two means are different or the same - i.e. H0: mu1 - mu2 = 0; H0: mu1 - mu2 is not 0 - set-up of formula for SE:

Answer 14

• SE = square root (s1^2/n1 + s2^2/n2)
• Use gaussian distribution if n1 and n2 > 30

Question 15

hypothesis testing - comparing to samples - t-test for comparing to sample means - formula

Answer 15

t-test = ((x1 bar - x2 bar) - 0) / SE = …
0 because H0 is mu1 - mu2 = 0

Question 16

reorder() function

Answer 16

The reorder() function reorders categories (e.g. region_names) based on the numerical data provided (e.g. total_crime)

Question 17

aes() function

Answer 17

In R, the aes() function is often used within other graphing elements to specify the desired aesthetics. The aes() function can be used in a global manner (applying to all of the graph’s elements) by nesting within ggplot()

Question 18

function qt() - explain

Answer 18

qt() provides the t-critical value (students may also talk about the probability that it expects, and the degrees of freedom)

returns the value on the x-axis below which contains the specified probability, or area under the t-distribution below that point. The pt() returns the probability that x is less than a specified value.

Question 19

Explain what the :: operator does

Answer 19

:: operator says package::function i.e. from the stated package, use the stated function.

Question 20

Explain what the functions xpnorm() and qnorm() do?

Answer 20

xpnorm() provides probability to the left and to the right of a specific z value in a Standard Normal distribution, i.e. 𝑃(𝑍 < 𝑧) as well as 𝑃(𝑍 > 𝑧) for a normally distributed standardized random variable z.

qnorm() for a given probability what is the corresponding z value of 𝑃(𝑍 < 𝑧)

Question 21

xxx_join and full_join(A,B)

Answer 21

full_join(A,B) - It joins tibble A and tibble B by a common column called colName automatically and results in all rows from both tibbles where matching rows are combined. In the case where there are no matching values the result is NA for the missing ones.

Question 22

Discuss the plots that allow you to check whether assumptions of a Linear Regression model have been satisfied - and which R function is that?

Answer 22

The function name is autoplot(). There are 3 plots for testing the residual behavior and they are:

• Residuals vs Fitted: shows if residuals are randomly scattered (have an average of zero). This is shown with the blue line which should be horizontal at 0.
• Normal Q-Q plot (points should be located on the diagonal – this would mean residuals are normally distributed.
• Scale location – should have horizontal blue line which would mean new have a case of constant variance with time.

Question 23

identify dplyr verbs?

Answer 23

filter() selects rows; group_by() groups by a given column; mutate() creates a
new column with the result of the transform on existing columns;

Question 24

Explain what the t.test() R function is used for?

Answer 24

.test() is used to test hypothesis. It provides information on:
- Confidence Interval
- t-stat
- p-value

Question 25

What does the separate function do?

Answer 25

separate() has been superseded in favour of separate_wider_position() and separate_wider_delim() because the two functions make the two uses more obvious, the API is more polished, and the handling of problems is better. Superseded functions will not go away, but will only receive critical bug fixes.

Given either a regular expression or a vector of character positions, separate() turns a single character column into multiple columns.

Question 26

what does pivot_longer do?

Answer 26

pivot_longer() “lengthens” data, increasing the number of rows and decreasing the number of columns. The inverse transformation is pivot_wider()

Question 27

function to make dataset tidy?

Answer 27

pivot_longer()

Question 28

Basic Data Types in R

Answer 28

Question 29

Untidy vs. Tidy Data

Answer 29

Question 30

DPLYR Package - key verbs

Answer 30

Key Verbs: select, filter, arrange, rename, mutate, summarise, group_by

Question 31

select()

Answer 31

select() pick columns (variables) directly by the names

Question 32

filter()

Answer 32

filter() pick rows (observations) by their values using logical conditions

Question 33

arrange()

Answer 33

arrange() reorders rows according to one of variable names while preserving order of columns

Question 34

Data Visualisation with ggplot2

Answer 34

Question 35

stats::t.test

Answer 35

Use a function from the stats package to produce the results from all three approaches in a single table (i.e. the CI approach, z/t-stat approach, p-value approach)

Question 36

reorder()

Answer 36

This function rearranges the levels of a factor variable based on a specified numeric summary (e.g., sum or mean of another variable). In the context of ggplot(aes(x = reorder())), it helps sort the bars or categories along the x-axis based on the values of another variable.

Question 37

geom_point()

Answer 37

The point geom is used to create scatterplots. The scatterplot is most useful for displaying the relationship between two continuous variables.

Question 38

geom_smooth()

Answer 38

Aids the eye in seeing patterns in the presence of overplotting. geom_smooth() and stat_smooth() are effectively aliases

Question 39

ggfortify library - autoplot()

Answer 39

Use the ggfortify library to plot 3 essential plots for residuals.

Question 40

huxreg() table

Answer 40

Question 41

favstats()

Answer 41

from mosaic library - “favstats” is short for “favorite statistics”: it will give you the some of the most popular summary statistics for numerical variables (mean, max, median, sd, etc.)

Question 42

What does geom mean?

Answer 42

Geometric objects (geoms) define the basic shape of the elements on the plot. Every geom has a default statistic.

Question 43

geom_col()

Answer 43

This function creates a bar plot where the heights of the bars represent the actual values of a variable (rather than counts or frequencies, which geom_bar() would use by default).

Question 44

coord_flip()

Answer 44

This function flips the x and y axes, effectively turning a vertical bar chart into a horizontal bar chart (or vice versa for other plot types).

Question 45

Give definition of the Central Limit Theorem

Answer 45

Question 46

Write down the distribution of the sample mean for…