To create multiple plots in one figure in Matplotlib, you would use the ___________ function.
- heatmap
- pairplot
- subplot
- violinplot
The 'subplot' function in Matplotlib is used to create multiple plots in a single figure. It allows you to arrange plots in a grid structure.
What is the full form of NMAR in the context of missing data?
- Never Missing At Random
- No Missing At Random
- Not Measured At Random
- Not Missing At Random
In the context of missing data, NMAR stands for Not Missing At Random.
The _________ library in Python allows for the creation of complex animated plots and provides widgets to allow for interactive plots.
- Bokeh
- Matplotlib
- Plotly
- Seaborn
Bokeh is a powerful library for creating interactive plots, including complex animated plots, and it includes support for widgets, making it a great tool for creating dynamic, interactive visualizations.
Which type of analysis is most commonly used for hypothesis testing?
- CDA
- Data Visualization
- EDA
- Predictive Modeling
CDA (Confirmatory Data Analysis) is most commonly used for hypothesis testing. While EDA is used to formulate hypotheses, CDA uses statistical techniques to confirm or reject these hypotheses.
How does negative kurtosis affect the tails of a data distribution?
- It has no effect on the tails of the distribution.
- It makes the distribution perfectly symmetrical.
- It makes the tails of the distribution heavier.
- It makes the tails of the distribution lighter.
Negative kurtosis, also known as platykurtic kurtosis, makes the tails of the data distribution lighter, indicating fewer extreme outliers. The distribution is flatter or more spread out than a normal distribution.
What type of plot is often used for visualizing the relationship between two continuous variables?
- Bar plot
- Box plot
- Histogram
- Scatter plot
Scatter plots are ideal for visualizing the relationship between two continuous variables. Each point in the scatter plot corresponds to the values of two variables.
What is the process of removing an entire row when any single data point within it is missing called?
- Listwise Deletion
- Mean Imputation
- Pairwise Deletion
- Regression Imputation
The process of removing an entire row when any single data point within it is missing is called 'Listwise Deletion'. Also known as 'Complete Case Analysis', this technique is straightforward and fast, but it can potentially discard valuable data and introduce bias if the missingness is not completely at random.
In the context of handling missing data, what does 'imputation' mean?
- Adding artificial data
- Deleting data points
- Filling in missing data with substituted values
- Transforming data
In the context of handling missing data, 'imputation' refers to the process of filling in missing data with substituted values. These values can be determined in a variety of ways such as using measures of central tendency (mean, median, mode), predictive models, or other techniques.
Imagine you are examining a correlation matrix and find that two variables have a correlation coefficient close to -1. What does this imply about the relationship between these two variables?
- Their relationship is random
- They are unrelated
- They have a strong negative relationship
- They have a weak positive relationship
A correlation coefficient close to -1 implies that the two variables have a strong negative relationship. This means that as one variable increases, the other decreases and vice versa.
What is the difference between skewness and kurtosis?
- Skewness measures asymmetry, kurtosis measures variability.
- Skewness measures center, kurtosis measures spread.
- Skewness measures spread, kurtosis measures center.
- Skewness measures symmetry, kurtosis measures tailedness.
The difference between skewness and kurtosis is that skewness measures the asymmetry of a data distribution around its mean, whereas kurtosis measures the "tailedness" of a data distribution. So, skewness is about the symmetry, and kurtosis is about the tails of the distribution.