Sir kyle

Question 1

What is data analytics?
a) The process of collecting and organizing data
b) The process of analyzing data to make decisions
c) The process of creating data
d) The process of deleting outdated data

Answer 1

b

Question 2

Why is data analytics important for businesses?
1/1
a) It helps in predicting market trends
b) It provides insights for better decision-making
c) It identifies business performance issues
d) All of the above

Answer 2

d

Question 2

Which type of analytics predicts future outcomes based on data?
1/1
a) Descriptive analytics
b) Diagnostic analytics
c) Predictive analytics
d) Prescriptive analytics

Answer 2

c

Question 2

What is descriptive analytics?
1/1
a) Analytics that explains what has happened
b) Analytics that predicts what will happen
c) Analytics that determines why something happened
d) Analytics that recommends actions to take

Answer 2

a

Question 3

Which of these is an example of structured data?
1/1
a) Social media posts
b) Email contents
c) Customer database with names and phone numbers
d) Images stored in a file

Answer 3

c

Question 4

What type of data visualization is best suited for showing parts of a whole?
1/1
a) Line chart
b) Pie chart
c) Scatter plot
d) Histogram

Answer 4

b

Question 5

Big Data refers to datasets that are…
1/1
a) Easy to store and manage
b) Too large and complex for traditional data-processing methods
c) Small but require a lot of computation
d) Structured and easy to analyze

Answer 5

b

Question 6

What is the purpose of A/B testing in data analytics?
1/1
a) To compare two versions of a product or feature to determine which performs better
b) To clean data
c) To automate the analysis process
d) To visualize complex data

Answer 6

a

Question 6

Which of the following describes prescriptive analytics?
1/1
a) Provides insights into why things happened
b) Describes what is happening in real-time
c) Recommends actions based on data analysis
d) Predicts future trends

Answer 6

c

Question 7

What is the significance of data governance in analytics?
1/1
a) To regulate the storage of data
b) To ensure data privacy, security, and compliance
c) To visualize large datasets
d) To improve the speed of data processing

Answer 7

b

Question 8

Which of the following is a type of data analytics?
1/1
A) Predictive Analytics
B) Descriptive Analytics
C) Prescriptive Analytics
D) All of the above

Answer 8

d

Question 9

What type of data is “Gender” in a dataset?
1/1
A) Quantitative
B) Qualitative
C) Continuous
D) Interval

Answer 9

b

Question 10

Which chart is most commonly used to show trends over time?
1/1
A) Pie Chart
B) Bar Chart
C) Line Chart
D) Scatter Plot

Answer 10

c

Question 11

In data cleaning, which process removes duplicate values in a dataset?
A) Normalization
B) Deduplication
C) Data Merging
D) Standardization

Answer 11

a

Question 12

What is the significance of data governance in analytics?
1/1
a) To regulate the storage of data
b) To ensure data privacy, security, and compliance
c) To visualize large datasets
d) To improve the speed of data processing

Answer 12

b

Question 13

Which of the following is NOT a form of data visualization?
1/1
a) Bar Chart
b) Line Graph
c) Base Graph
d) Scatter Plot

Answer 13

c

Question 14

Which chart is best suited for showing the distribution of data across different categories?
1/1
a) Line chart
b) Pie chart
c) Bar chart
d) Scatter plot

Answer 14

c

Question 15

When creating a histogram, the X-axis represents:
1/1
a) Data frequency
b) Data values or ranges
c) Percentages
d) None of the above

Answer 15

b

Question 16

In a histogram, what does the height of each bar represent?
1/1
a) The sum of data values in that range
b) The frequency or count of data in a specific range
c) The total data collected
d) The average of the data points in that bin

Answer 16

b

Question 17

If the bars in a histogram are skewed to the right, what does this indicate about the distribution of the data?
1/1
a) Symmetric distribution
b) Positively skewed distribution
c) Negatively skewed distribution
d) Uniform distribution

Answer 17

b

Question 17

Which measure of central tendency is most affected by outliers?
1/1
a) Mean
b) Median
c) Mode
d) All are equally affected

Answer 17

a

Question 18

The median is defined as:
1/1
a) The average of all values
b) The most frequently occurring value
c) The middle value when data is ordered
d) The range of the dataset

Answer 18

c

Question 19

When would the median be a better measure of central tendency than the mean?
1/1
a) When data is symmetrically distributed
b) When data has outliers or is skewed
c) When data is categorical
d) When data contains repeated values

Answer 19

b

Question 19

What does the mean of a dataset represent?
1/1
a) The most frequently occurring value
b) The value that divides the data into two equal parts
c) The average of all data points
d) The value with the highest frequency

Answer 19

c

Question 20

If the mean and median of a dataset are equal, what type of distribution does the data likely have? 1/1 a) Skewed to the left b) Skewed to the right c) Relatively Symmetric d) Uniform distribution

Answer 20

c

Question 21

Which measure of central tendency divides the dataset into two equal parts? 1/1 a) Mean b) Median c) Mode d) Interquartile range

Answer 21

b

Question 22

In a dataset where the mean is greater than the median, what can you infer about the shape of the distribution? 1/1 a) It is symmetric b) It is positively skewed (right-skewed) c) It is negatively skewed (left-skewed) d) It is normally distributed

Answer 22

b

Question 22

When analyzing income data, which measure of central tendency is typically preferred and why? 1/1 a) Mean, because it includes all data values b) Median, because it is less influenced by extreme outliers c) Mode, because it represents the most common income level d) Mean, because it minimizes the impact of variance

Answer 22

b

Question 22

In a dataset with outliers, why might the median be a better measure of central tendency than the mean? 1/1 a) The median reflects all values in the dataset b) The mean is distorted by extreme values, while the median is not c) The mode is more reliable than the mean d) The mean and median are always equal

Answer 22

b

Question 23

1. Questions 2. Data Collection 3. Data Cleaning 4. Data Analysis 5. Data Interpretation

Answer 23

Data Analytics Workflow

Question 23

Why are measures of central tendency important for summarizing large datasets? 1/1 a) They reduce the complexity of data by providing a single representative value b) They eliminate the need to analyze individual data points c) They measure the spread of the data d) They provide insight into data variability

Answer 23

a

Question 23

1965, Intel co-founder ____ predicted that the number of transistors on a chip would double roughly every two years, with a minimal rise in cost1

Answer 23

Gordon Moore

Question 24

“I would expect that next year, people will share twice as much information as they share this year, and next year, they will be sharing twice as much as they did the year before”

Answer 24

Mark Zuckerberg

Question 25

characteristic of members of a population e.g., market share, revenue, season, Bike_Rentals, temperature, date, weather condition

Answer 25

Variables

Question 25

Observations can be named without particular order or ranking imposed on the data. Words, letters, and even numbers are used to classify the data

Answer 25

Nominal Value

Question 25

observations of variable e.g., 11%, $225M, summer, 985, 23.5˚, 1/12/2011, mcdonalds

Answer 25

Data

Question 25

contains variables and observations Array (rows and columns)

Answer 25

Data Set

Question 26

Indicates an actual amount (numerical). The order and the difference between the variables can be known. It limitation is it has no “true zero”.

Answer 26

Interval Level

Question 26

The degree to which all required data is known.

Answer 26

Completeness

Question 26

Describes ranking or order. The difference or ratio between rankings may not always be the same.

Answer 26

Ordinal Value

Question 26

It has the same properties as the interval level. The order and difference can be described. Additionally, it has a true zero and the ratio between two points has a meaning

Answer 26

Ratio Level

Question 26

Accuracy. Ensure your data is close to the true values (real-world objects it represents). Validity. If it measures what it is supposed to measure Completeness. The degree to which all required data is known. Consistency. Ensure your data is consistent within the same dataset and/or across multiple data sets. Uniformity. The degree to which the data is specified using the same unit of measure.

Answer 26

DATA QUALITY DIMENTIONS

Question 26

Ensure your data is close to the true values (real-world objects it represents).

Answer 26

Accuracy

Question 26

If it measures what it is supposed to measure

Answer 26

Validity

Question 27

Right positively skewed: The right tail is longer Values of data extend to the right

Answer 27

Skewed to the RighT

Question 27

Ensure your data is consistent within the same dataset and/or across multiple data sets.

Answer 27

Consistency

Question 27

Gather data from various sources, such as databases, files, APIs, or surveys. Ensure that the data collected is relevant to your research question or analysis objectives.

Answer 27

Data Collection and Acquisition

Question 27

The degree to which the data is specified using the same unit of measure.

Answer 27

Uniformity

Question 27

Examine the raw data to get a sense of its structure and contents. Check for missing values, outliers, and anomalies that may require attention..

Answer 27

Data Inspection

Question 27

Address missing data by deciding whether to fill in missing values or remove records with missing values. Correct any data entry errors, inconsistencies, or outliers, duplicated records. Standardize data formats (e.g., date formats, data types) to ensure consistency.

Answer 27

Data Cleansing

Question 27

Encode categorical variables into numerical format using techniques like one-hot encoding or label encoding. Normalize or scale numerical features if necessary to bring them to a common scale.

Answer 27

Data Transformation

Question 27

Combine data from multiple sources if needed, ensuring that there are common identifiers to merge the data correctly.

Answer 27

Data Integration

Question 27

Create visualizations to explore the data further and identify patterns, relationships, or outliers. Visualization helps in understanding the data's characteristics and guiding further analysis.

Answer 27

Data Visualization

Question 27

Data Creation/Collection Data Ingestion (ETL) Data Storage Data Presentation and Visualization Data Sharing and Distribution Data Archiving and Retention Data Backup and Disaster Recovery Data Deletion and Disposal

Answer 27

Data Life Cycle

Question 27

Left negatively skewed: The left tail is longer Values of data extend to the left

Answer 27

Skewed to the left