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Statistics 101 Cognitive Class Exam Quiz Answers

Statistics 101 Cognitive Class Certification Answers

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:

• 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

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

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

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

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

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 the science of collecting, analyzing, interpreting, and presenting data. It’s a fundamental tool used in various fields such as science, business, economics, engineering, and social sciences. In this introductory overview, let’s cover some key concepts:

1. Descriptive Statistics: This branch focuses on summarizing and describing the characteristics of a dataset. It includes measures like mean, median, mode, variance, and standard deviation.
2. Inferential Statistics: This branch involves making inferences or predictions about a population based on a sample of data. It includes techniques like hypothesis testing, confidence intervals, and regression analysis.
3. Population and Sample: A population is the entire group of individuals or objects that we’re interested in studying, while a sample is a subset of the population that we actually observe and collect data from.
4. Variables: In statistics, a variable is any characteristic or quantity that can take different values. Variables can be classified as either categorical (e.g., gender, color) or numerical (e.g., height, weight).
5. Types of Data: Data can be classified into two main types: qualitative data, which describes qualities or characteristics, and quantitative data, which consists of numerical measurements.
6. Probability: Probability theory is essential in statistics for quantifying uncertainty. It helps us understand the likelihood of various outcomes and events.
7. Statistical Distributions: Distributions describe how the values of a variable are spread out. Common distributions include the normal distribution, binomial distribution, and Poisson distribution.
8. Statistical Tests: These are procedures used to make decisions about a population based on sample data. Examples include t-tests, chi-square tests, and ANOVA.
9. Data Visualization: Visualizing data is crucial for understanding patterns, trends, and relationships. Graphs and charts like histograms, scatter plots, and bar charts are commonly used for this purpose.
10. Ethical Considerations: Statistics is not just about crunching numbers; it also involves ethical considerations, such as ensuring data privacy, avoiding bias, and accurately representing findings.

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