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web.groovymark@gmail.com
- November 21, 2024
Question 01
In statistics, what is the purpose of using a “sampling technique”?
a) To increase the size of the dataset
b) To systematically select members from a population for analysis
c) To eliminate bias from data
d) To visualize data trends
Correct Answer: b) To systematically select members from a population for analysis
Explanation: Sampling techniques are methods used to select individuals from a population, ensuring that the sample is representative for accurate analysis.
Question 02
What type of data is measured on a “ratio scale”?
a) Data without a true zero
b) Data with meaningful zero and allows for comparisons of magnitude
c) Categorical data
d) Data that can only be ranked
Correct Answer: b) Data with meaningful zero and allows for comparisons of magnitude
Explanation: The ratio scale has an absolute zero point, meaning ratios are meaningful (e.g., weight, height) and comparisons can be made.
Question 03
What is the significance of the “mean” in a dataset?
a) It is always equal to the median.
b) It represents the most frequently occurring value.
c) It is the average of all values, providing a measure of central tendency.
d) It shows the range of values in the dataset.
Correct Answer: c) It is the average of all values, providing a measure of central tendency.
Explanation: The mean is calculated by adding all values in a dataset and dividing by the number of values, reflecting the central tendency of the data.
Question 04
When should you use a frequency distribution table?
a) When you need to visualize data trends
b) When summarizing and organizing data by frequency of occurrence
c) When performing complex calculations
d) When analyzing qualitative data
Correct Answer: b) When summarizing and organizing data by frequency of occurrence
Explanation: A frequency distribution table organizes data into categories and shows how many observations fall into each category, aiding in data analysis.
Question 05
What does a “bar chart” typically represent?
a) Parts of a whole
b) Trends over time
c) The frequency of categories
d) Relationships between variables
Correct Answer: c) The frequency of categories
Explanation: Bar charts display the frequency of different categories using bars, allowing for easy comparison between the categories.
Question 06
What does the term “cumulative frequency” represent in data analysis?
a) The total number of observations in a dataset
b) The frequency of each category in isolation
c) The running total of frequencies up to each category
d) The difference between the highest and lowest values
Correct Answer: c) The running total of frequencies up to each category
Explanation: Cumulative frequency summarizes how many observations fall below or at each point, providing insight into the distribution of the data.
Question 07
In Excel, which function would you use to calculate the average of a range of cells?
a) =SUM
b) =AVERAGE
c) =COUNT
d) =MAX
Correct Answer: b) =AVERAGE
Explanation: The AVERAGE function computes the mean of a specified range, summarizing the central tendency of the values in that range.
Question 08
What is the primary function of “inferential statistics”?
a) To summarize data
b) To describe the population
c) To make predictions about a population based on sample data
d) To visualize data
Correct Answer: c) To make predictions about a population based on sample data
Explanation: Inferential statistics allows researchers to draw conclusions and make inferences about a population from observations collected from a sample.
Question 09
Which type of sampling ensures that subgroups are proportionately represented in the sample?
a) Convenience sampling
b) Simple random sampling
c) Stratified sampling
d) Cluster sampling
Correct Answer: c) Stratified sampling
Explanation: Stratified sampling divides the population into strata (subgroups) and samples from each stratum, ensuring representation of all subgroups.
Question 10
How is the mode defined in statistics?
a) The average of the dataset
b) The value that appears most frequently
c) The midpoint of the dataset
d) The range of the dataset
Correct Answer: b) The value that appears most frequently
Explanation: The mode is the most common value in a dataset and is particularly useful in categorical data analysis.
Question 11
What does “data cleaning” entail in the context of data analysis?
a) Summarizing data
b) Removing duplicates and correcting errors in the dataset
c) Analyzing trends
d) Visualizing data
Correct Answer: b) Removing duplicates and correcting errors in the dataset
Explanation: Data cleaning is essential for ensuring the accuracy and quality of data before analysis, helping to eliminate errors and inconsistencies.
Question 12
What is a key advantage of using a “pie chart”?
a) It shows trends over time.
b) It illustrates proportions of a whole.
c) It compares categories effectively.
d) It summarizes large datasets.
Correct Answer: b) It illustrates proportions of a whole.
Explanation: Pie charts effectively visualize the parts of a whole, allowing viewers to see how individual categories contribute to the total.
Question 13
What does the “standard deviation” measure in a dataset?
a) The average value
b) The dispersion or variability of data points from the mean
c) The frequency of each category
d) The total number of observations
Correct Answer: b) The dispersion or variability of data points from the mean
Explanation: Standard deviation quantifies how much individual data points deviate from the mean, indicating the degree of spread in the dataset.
Question 14
Which of the following statements about continuous variables is true?
a) They can only take on distinct values.
b) They can assume an infinite number of values within a range.
c) They are always whole numbers.
d) They cannot be measured.
Correct Answer: b) They can assume an infinite number of values within a range.
Explanation: Continuous variables can take any value within a specified range, such as measurements of height, weight, or temperature.
Question 15
What does “data normalization” help achieve?
a) It cleans data by removing duplicates.
b) It ensures that data is presented in a consistent format.
c) It scales data to a common range without distorting differences.
d) It aggregates data into summary statistics.
Correct Answer: c) It scales data to a common range without distorting differences.
Explanation: Normalization adjusts data to a common scale, allowing for more accurate comparisons and analyses between datasets.
Question 16
What does a histogram visualize?
a) Categorical data
b) Frequency distribution of numerical data
c) Trends over time
d) Proportions of a whole
Correct Answer: b) Frequency distribution of numerical data
Explanation: A histogram represents the frequency distribution of numerical data across defined intervals (bins), providing insight into data distribution.
Question 17
In Excel, which function would you use to find the maximum value in a range?
a) =SUM
b) =AVERAGE
c) =COUNT
d) =MAX
Correct Answer: d) =MAX
Explanation: The MAX function identifies the largest value from a specified range of numbers in Excel.
Question 18
What type of analysis is most appropriate for determining the effect of one variable on another?
a) Correlational analysis
b) Descriptive analysis
c) Inferential analysis
d) Causal analysis
Correct Answer: d) Causal analysis
Explanation: Causal analysis investigates the cause-and-effect relationship between variables, helping to understand how one variable influences another.
Question 19
What does the term “outlier” refer to in a dataset?
a) A value that is very common
b) A value that deviates significantly from other observations
c) The average value of a dataset
d) A value that appears frequently
Correct Answer: b) A value that deviates significantly from other observations
Explanation: Outliers are extreme values that can skew data analysis and should be investigated to understand their impact.
Question 20
What is the best way to visualize the relationship between two quantitative variables?
a) Bar chart
b) Pie chart
c) Scatter plot
d) Histogram
Correct Answer: c) Scatter plot
Explanation: A scatter plot displays individual data points for two quantitative variables, allowing for analysis of relationships and correlations.
