Business Analytics Final Review Flashcards

Front

What is the purpose of data normalization in EDA?

Back

To standardize data to a common scale

Answer explanation

Data normalization in EDA is used to standardize data to a common scale, which helps in comparing different variables effectively. This ensures that no single variable dominates due to its scale, making analysis more reliable.

Front

Which statistical measure quantifies the strength and direction of a linear relationship between two variables?

Back

Correlation coefficient

Answer explanation

The correlation coefficient quantifies the strength and direction of a linear relationship between two variables, indicating how closely they move together. Other options like standard deviation and variance measure variability, not correlation.

Front

What does the law of large numbers state?

Back

Sample means converge to the population mean as sample size increases

Answer explanation

The law of large numbers states that as the sample size increases, the sample means will get closer to the population mean. This makes the choice 'Sample means converge to the population mean as sample size increases' correct.

Front

In R, which package is commonly used for data manipulation and transformation?

Back

dplyr

Answer explanation

The 'dplyr' package in R is specifically designed for data manipulation and transformation, providing functions for filtering, selecting, and summarizing data. Other options like 'ggplot2' and 'caret' serve different purposes.

Front

Which statistical test would you use to compare means among three or more groups?

Back

ANOVA

Answer explanation

ANOVA (Analysis of Variance) is the appropriate test for comparing means across three or more groups, as it assesses whether there are statistically significant differences between the group means.

Front

What type of chart is best for displaying the distribution of a continuous variable?

Back

Histogram

Answer explanation

A histogram is the best choice for displaying the distribution of a continuous variable as it groups data into bins, allowing for visualization of frequency and distribution patterns. Other charts are less effective for this purpose.

Front

What does 'data wrangling' involve in EDA?

Back

Transforming and mapping data from one format to another

Answer explanation

Data wrangling in EDA primarily involves transforming and mapping data from one format to another, ensuring it is clean and structured for analysis. This is crucial for effective exploratory data analysis.

Front

Which R function is used to create a data frame?

Back

data.frame()

Answer explanation

The correct function to create a data frame in R is data.frame(). The other options, create.dataframe(), make.df(), and new.dataframe(), do not exist in R, making data.frame() the only valid choice.

Front

In hypothesis testing, what does the significance level (α) represent?

Back

The probability of rejecting a true null hypothesis

Answer explanation

The significance level (α) represents the probability of rejecting a true null hypothesis, also known as a Type I error. It indicates how much risk of error the researcher is willing to accept when making a decision.

Front

Which visualization technique is best for showing the relationship between two continuous variables?

Back

Scatter plot

Answer explanation

A scatter plot is the best visualization technique for showing the relationship between two continuous variables, as it displays individual data points and reveals patterns, trends, and correlations effectively.