**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.