Module 5 - Analyze the Data Using Statistics

Question 1

Differentiate samples vs population

Answer 1

• A population is the whole set of values or individuals you are interested in, while a sample is a subset of the population.
• Measurements on the entire population are often too complex or impossible, so representative samples are used to draw conclusions about the population.
• The numbers we’ve obtained when using a population are called parameters, while the numbers we’ve obtained when working with a sample are called statistics.
• Population parameters are more precise and accurate, as they are calculated using all available data.
• Researchers use samples to learn about populations.

Question 2

are used to describe or summarize the values and observations of a data set.

Answer 2

Descriptive statistics

Question 3

Describe why is this a Descriptive Statistics: For example, a fitness tracker logged a person’s daily steps and heart rate for a 10-day period. If the person met their fitness goals in 6 out of the 10 days, then they were successful 60% of the time. Over that 10-day period, you could observe that the person’s heart rate was a maximum of 140 beats per minute (bpm), but an average of 72 bpm. These observations would be descriptive statistics that could be used to describe and simplify the data set.

Answer 3

(Explain)

Question 4

might include the total number of data points in a data set, the range of values that exist for those numeric data points, or the number of times a given value appears in a data set.

Answer 4

Basic descriptive statistics

Question 5

may also answer questions about the occurrence of trends.

Answer 5

Descriptive statistics

Question 6

The answers to these questions can be provided in numerical or graphical formats.

Answer 6

Descriptive statistics

Question 7

Results of descriptive statistics are often represented in?

Answer 7

pie charts, bar charts or histograms.

Question 8

One important point to note is that while descriptive statistics describe the current or historical state of the observed population, it does not allow for?

Answer 8

• comparison of groups
• conclusions to be drawn
• predictions to be made about data sets that are not in the population

Question 9

is the process of collecting, analyzing and interpreting the data gathered from a sample to generalize or predict something about a population.

Answer 9

Inferential statistics

Question 10

are a helpful way to make quick judgements about the quality of a sample.

Answer 10

Graphs of descriptive statistics

Question 11

A number of inferential analyses are very commonly used in big data analytics which are?

Answer 11

Cluster analysis, Association analysis, Regression analysis

Question 12

Used to find groups of observations that are similar to each other

Answer 12

Cluster analysis

Question 13

Used to find co-occurrences of values for different variables

Answer 13

Association analysis

Question 14

Used to quantify the relationship, if any, between the variations of one or more variables

Answer 14

Regression analysis

Question 15

What are the questions to consider when picking a data visualization?

Answer 15

• How many variables are you going to show?
• How many data points are in each variable?
• Is your data over time or are you comparing data points at a single point in time?

Question 16

Use this visualization when you have a continuous set of data, the number of data points is high, and/or you would like to show a trend in the data over time.

Answer 16

Line Charts

Question 17

Give some examples of the uses of Line Charts

Answer 17

• Quarterly sales for the past five years
• Number of customers per week in the first year of a new retail shop
• Change in a stock’s price on one day, from opening to closing bell

Question 18

What are the best practices for Line Charts?

Answer 18

• Label the axes.
• Plot time on the x-axis (horizontal) and the data values on the y-axis (vertical). Use a solid line (rather than a broken line) to emphasize continuity of the data.
• Keep the number of data sets to a minimum. There should be a very good reason for plotting more than four lines. If needed, add a legend to help the audience understand what they are viewing.
• Remove or minimize gridlines to reduce distraction. Consider using no gridlines except to emphasize certain values or time periods.
• Modify the y-axis starting point to obtain something close to a 45-degree slope in one or more of the lines. This ensures you emphasize the change in the data without introducing distortions that dramatize the visualization.

Question 19

This type of chart is probably the most common chart type used to display the values of a specific variable across similar categories.

Answer 19

Column Chart

Question 20

Give some examples of Column Chart

Answer 20

• Populations of the BRICS nations (Brazil, Russia, India, China, and South Africa)
• Last year’s sales for the top four car companies
• Average student test scores for six math classes

Question 21

What are the best practices of column chart ?

Answer 21

• Label the axes.
• If changes over time are being shown, time should be plotted on the x-axis.
• If time is not part of the data, consider ordering the data so that column heights ascend or descend.
• Fill the columns with a solid color. To highlight one column, consider using an accent color and make all the other columns the same color.
• Column charts are best when there are no more than seven categories on the horizontal axis. This will help the viewer clearly see the value for each column.
• Start the value of the y-axis at zero to accurately reflect the full value of each column.
• The spacing between columns should ideally be roughly half the width of a column.

Question 22

are similar to column charts except they are positioned horizontally and hence used slightly differently

Answer 22

Bar Charts

Question 23

What are some examples of Bar Charts?

Answer 23

• Gross domestic product (GDP) of the 25 highest-producing nations in a given year
• Number of cars sold by each sales representative in a group
• Exam scores for each student in a math class

Question 24

What are some best practices of Bar Charts?

Answer 24

• Label the axes.
• Consider ordering the bars so that the lengths go from longest to shortest. The meaning of the data shown will most likely determine whether the longest bar should be on the bottom or the top for greatest impact or easiest understanding.
• Fill the bars with a solid color. To highlight one bar, consider using an accent color and make all the other bars the same color.
• Start the value of the x-axis at zero to accurately reflect the full value of each bar.
• The spacing between bars should ideally be roughly half the width of a bar.

Question 25

are used to show the composition of a total. Segments of different sizes visually represent percentages of that total. The sum of the segments must equal 100%.

Answer 25

Pie charts

Question 26

What are some examples of Pie Charts?

Answer 26

• Annual expenses for a corporation (e.g., rent, administrative, utilities, production)
• A country’s energy sources (e.g., oil, coal, gas, solar, wind)
• Survey results for a group’s favorite type of movie (e.g., action, romance, comedy, drama, science fiction)

Question 27

What are some example of Pie Charts?

Answer 27

• Limit the number of categories so that the viewer can easily differentiate between segments and their meaning in relation to each other. After ten or more segments, the slices begin to lose meaning and impact.
• If necessary, consolidate smaller segments into one segment with a label such as “Other” or “Miscellaneous”.
• Use a different color or gray scale for each segment.
• Order the segments clockwise according to size.
• Make sure the value of all segments equals 100%.

Question 28

are very popular for visualizing correlations, or to show the distribution of many data points. They are also useful for demonstrating clustering or identifying outliers in the data.

Answer 28

Scatter Plots

Question 29

What are some examples of Scatter Plots?

Answer 29

• Comparing life expectancy to GDP for each country in a group
• Comparing the daily sales of ice cream at a given location to the average outside temperature
• Comparing the weight to the height of each person in a group

Question 30

What are some best practices for scatter plots?

Answer 30

• Label the axes.
• Make sure the data set is large enough to provide visualization for clustering or outliers.
• Start the value of the y-axis at zero to accurately reflect the full values of the data. The value of the x-axis will depend on the data. For example, age ranges of ice cream customers might be labeled on the x-axis, and there would be no need to start at zero years of age.
• If scatter plot shows a correlation between values on the x- and y-axes, consider adding a trend line.
• Do not include more than two trend lines.

Question 31

is a data point that does not fit the rest of the data. It lies outside of a cluster and does not follow the same pattern.

Answer 31

outlier

Question 32

In the data analysis process, outliers that are the result of mistakes can lead to?

Answer 32

anomalies

Question 33

why investigating anomalies is a very important part of the data cleaning process?

Answer 33

it ensures that data can be analyzed effectively and generate accurate and valid results.

Question 34

With small data sets it may be relatively easy to spot outliers by ?

Answer 34

sorting or filtering the data.

Question 35

Two common types of data visualization used to find outliers are ?

Answer 35

scatter plots and box plots.

Question 36

is a very powerful data analysis tool within Excel and is great when you need to find information in a large spreadsheet or if you are consistently looking for the same type of information.

Answer 36

VLOOKUP

Question 37

VLOOKUP is an abbreviation of ?

Answer 37

vertical lookup

Question 38

A VLOOKUP function consists of 4 key pieces of information which are:

Answer 38

1. The value to search for
2. The range to search in
3. The column in the range that contains the value you want the function to return
4. An indication of whether the function should return an approximate match (TRUE, in the function) or only an exact match (FALSE) of the return value. The default for VLOOKUP is an approximate match if FALSE is not specified in the function.

Question 39

Does this make sense?

Answer 39

VLOOKUP searches for a value in the leftmost column of a table and, when the value is found, returns information from the same row but in another column.

Question 40

Does this make sense?

Answer 40

With XLOOKUP, you can look in any column (not only the leftmost in a table) for a search term and return a result from the same row. One difference is that XLOOKUP defaults to returning an exact match, whereas VLOOKUP defaults to closest match unless the FALSE keyword is used. In this course, you may use either VLOOKUP or XLOOKUP to obtain the desired results if they are both available in the spreadsheet tool you are using.
Note: XLOOKUP is not backward compatible, so worksheets using XLOOKUP may not be usable in earlier versions of Excel.

Question 41

What does vlookup contains?

Answer 41

=VLOOKUP(lookup_value, table_array, col_index_num, [range_lookup])