Statistics 101 Cognitive Class Exam Quiz Answers

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Enroll Here: Statistics 101 Cognitive Class Exam Quiz Answers

Statistics 101 Cognitive Class Certification Answers

Module 1 – Welcome to Statistics Quiz Answers – Cognitive Class

Question 1: Which one of the following is not an example of statistics?

The sweet smell of success
Monthly housing prices in a city
Traffic noise at a busy intersection
Annual unemployment rate in a country

Question 2: Which of the following statements is true? One can estimate the votes for a presidential candidate in a forthcoming election by:

Asking your barber
Conducting a poll of a random sample of the voting age population
Asking your favourite university professor about who is going to win
Asking the cab drivers in a city of their vote preference

Question 3: Which of the following is not a type of data visualization? (Pick the most appropriate answer)

An organization chart
A pie chart
A time series plot
A bar chart

Module 2 – Descriptive Statistics Quiz Answers – Cognitive Class

Question 1: Which of the following is not a cross-sectional data set?

Monthly survey of consumer confidence
National Census conducted every 5 or 10 years
Weekly data on average temperature
A survey of student satisfaction conducted at the end of the course

Question 2: Which of the following is an example of time series data?

Number of dolphins in the Pacific Ocean
Average batting average of a baseball player
Number of trees in Jardin du Luxemburg in Paris
Annual average housing price in New York

Question 3: Which of the following is an example of multivariate data?

Vital signs recorded for a new born baby
Number of songs played in a day by your favourite radio station
Daily temperature recorded by a monitoring station in Antarctica
Number of words spoken by President Donald Trump in his inaugural speech

Module 3 – Advanced Descriptive Statistics Quiz Answers – Cognitive Class

Question 1: What is a suitable way to display the average income earned by men and women in a city?

A scatter plot
A pie chart
A histogram
A bar chart

Question 2: What is a suitable way to display relationship between two continuous variables?

A scatter plot
A pie chart
A histogram
A bar chart

Question 3: What’s the best way to display median and outliers?

A bubble chart
A time series plot
A box plot
A scatter plot

Module 4 – Visualization Quiz Answers – Cognitive Class

Question 1: What is the best way to display daily temperature for a city?

A histogram
A pie chart
A Box plot
A line plot

Question 2: What extra step is needed to display two related time series variables that differ greatly in magnitude?

Use two axes to display the lines
Plot them by colouring the lines with different colours
Plot the lines with different thickness
Plot them separately in two charts

Question 3: When the sum of two or more categories equals 100, what chart type is ideally suited for displaying data?

A line chart
A pie chart
A box plot
A histogram

Module 5 – “From Start to Finish: Beauty Pays Data” Quiz Answers – Cognitive Class

Question 1: When using sample data with weights, it is important to compute statistics by:

Filtering the data with the weight variable
Weighting the data with the appropriate variable
Ignoring the weights
None of the above

Question 2: When multiple observations are reported for each respondent in the data set, to compute statistics for variables about the respondents, one must:

Ignore the presence of duplicates and compute statistics as usual
Weight data by duplicates
Remove duplicates before running analysis
None of the above

Question 3: To be able to trace one’s steps, one must:

Generate and record syntax for every command executed for the analysis
Note steps taken for the analyses in a notebook
Use mouse for point and click to undertake the analysis
None of the above

Statistics 101 Final Exam Answers – Cognitive Class

Question 1: What is meta data?

Data about metal fatigue
The metabolism data in a clinical trial
The data about metamorphism
It’s the data about data

Question 2: Which of the following is not an example of big data?

Number of photographs uploaded to the internet every day
The emails sent daily from your email provider
The number of big basketball players in NBA (National Basketball Association)
Weekly data about individual credit card transactions registered for your local credit card company

Question 3: SPSS is ideally suited to analyze data stored in:

Books as words and paragraphs
Digital video files of Hollywood movies
Tables as rows and columns
Digital audio files of music records

Question 4: Reproducibility in statistical analysis requires one to use statistical software that supports:

Free usage for analysis
Syntax (script) based analysis
Tabular output of results
A point and click environment

Question 5: Which of the following is an example of categorical data?

Number of fire hydrants in a city
Number of children at a kindergarten
Length of the river Nile
Mode of travel to work

Question 6: Which of the following is not an example of ordinal data?

Ranking of athletes in an Olympic competition
Number of trees in a park
Level of happiness on a scale of 1 to 5
Street numbers

Question 7: Which of the following is an example of interval data?

The ethnicity of a person
“None”, “Some”, “Frequent” – representing the frequency of exercise
First, second and third rankings in a sports competition
Weight

Question 8: For a survey of student satisfaction in a course, the population comprises:

All students enrolled in the course
All male students registered in the department
All A+ students enrolled in the course
All students registered at the university

Question 9: A mean is meaningful for the following type of data

Audio data
Ordinal data
Ratio data
Categorical data

Question 10: Median represents a value in the data set where:

Half of the observations are above the median and the other half below it
Most observations are negative
Half of the observations are known and the other half not known
Most observations are positive

Question 11: If the standard deviation of a variable is larger than the mean, the variable depicts:

Fluidity
Low variance
Smoothness
High variance

Question 12: A histogram is a graphical display of how a variable is

Observed
Displayed
Distributed
Recorded

Question 13: The following type of computation is suited for categorical data:

Proportions
Standard deviations
Histogram
Averages

Question 14: The relationship between two categorical variables can be captured by:

Standard deviation
A crosstabulation
A bar chart
A histogram

Question 15: The probability of getting a 2 by rolling TWO six-sided dice (with sides labeled as 1, 2, 3, 4, 5, 6) is

1/36
1/18
2
2/36

Question 16: What is the best way to determine the significance of relationship between two categorical variables?

A regression model
A Pearson Correlation test
A Chi-square test
A t-test

Question 17: If two continuous variables are positively correlated, their scatter plot will depict:

A flat line
A downward sloping curve
An upward sloping curve
None of the above

Question 18: What is the best way to determine the significance of relationship between two continuous variables?

A regression model
A Pearson Correlation test
A Chi-square test
A t-test

Question 19: A good chart should not be missing the following:

A self-explanatory variable title
Thick borders
A dark background colour
Bright colours

Question 20: What is the best practice to display axes labels?

Use self-explanatory variables
Use variable names
Use bold font to highlight labels
Don’t use any labels

Introduction to Statistics 101

Statistics is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It plays a crucial role in various fields such as science, business, economics, social sciences, and more. Here are some key concepts and terms related to statistics:

Descriptive Statistics:
- Measures of Central Tendency: Mean, Median, Mode
- Measures of Dispersion: Range, Variance, Standard Deviation
Inferential Statistics:
- Hypothesis Testing: A method for making inferences about a population based on a sample of data.
- Confidence Intervals: A range of values used to estimate the true value of a population parameter.
Probability:
- Probability Distributions: Describes the likelihood of obtaining different values in a population.
- Random Variables: Variables whose values are determined by chance.
Regression Analysis:
- Linear Regression: Examines the relationship between two or more variables.
- Multiple Regression: Examines the relationship between multiple independent variables and a dependent variable.
ANOVA (Analysis of Variance):
- A statistical method used to compare means among different groups.
Statistical Software:
- Tools like R, Python (with libraries like NumPy, Pandas, and Statsmodels), SAS, SPSS, and others are commonly used for statistical analysis.
Sampling Techniques:
- Random Sampling, Stratified Sampling, Cluster Sampling, Convenience Sampling, etc.
Statistical Tests:
- t-test: Compares the means of two groups to determine if there is a significant difference.
- Chi-squared test: Tests the independence of categorical variables.
- ANOVA (Analysis of Variance): Tests the equality of means across multiple groups.
Bayesian Statistics:
- A statistical paradigm that involves updating probabilities based on new evidence.
Data Types:
- Qualitative Data: Categorical data without a numerical value.
- Quantitative Data: Numerical data that can be measured and counted.
Population vs. Sample:
- Population: The entire set of individuals or instances about whom information is desired.
- Sample: A subset of the population used to make inferences about the entire population.

Statistics is a powerful tool for making informed decisions, drawing conclusions from data, and testing hypotheses. It provides a framework for understanding variability and uncertainty in various phenomena.