What kind of bias might be introduced into a model if missing data is not appropriately addressed?
- All above.
- Confirmation bias.
- Observation bias.
- Sampling bias.
Inappropriate handling of missing data can lead to sampling bias, where the model is trained on a non-representative subset of the data, hence the model's predictions could be biased.
What are the key components to focus on during the 'communicate' step in EDA?
- Cleaning and transforming data
- Ensuring the insights are effectively conveyed to relevant stakeholders
- Only sharing the raw data
- Reordering the EDA steps
During the communication phase of the EDA process, the key focus is to ensure that the insights, findings, or conclusions drawn from the analysis are effectively conveyed to the relevant stakeholders. This might involve presenting the insights in a simple and understandable manner, making use of visualizations, and tailoring the communication to the audience's needs and context.
If a row with at least one missing value is deleted, the process is known as _____.
- Listwise Deletion
- Mean Imputation
- Mode Imputation
- Pairwise Deletion
If a row with at least one missing value is deleted, the process is known as 'listwise deletion'. Although it is a simple method, it can result in loss of valuable information if the missing data is not completely random.
Given a set of data that follows a Binomial Distribution, how would you estimate the parameters of the distribution?
- By applying the Central Limit Theorem
- By computing the mean and standard deviation
- By taking the square root of the data
- By using a chi-squared test
The parameters of a Binomial Distribution can be estimated by computing the mean and standard deviation of the data.
The _____ of a histogram can significantly influence the representation of data.
- Bin width
- Color
- Shape
- Size
The bin width of a histogram is critical in data representation. If it's too large, it may smooth over the details of the distribution. If it's too small, the histogram may be too cluttered or noisy.
Outliers can potentially _______ the interpretation of the data.
- Complicate
- Improve
- Simplify
- Skew
Outliers can skew the interpretation of the data. They can affect the mean and standard deviation, thus distorting the overall understanding of the data.
Which measure of central tendency is most affected by outliers in the data set?
- All of them
- Mean
- Median
- Mode
The "Mean" or the average is the measure of central tendency that is most affected by outliers in a data set. The mean considers every value in the data set, and hence, extreme values (outliers) can significantly affect its value.
The data missingness mechanism that could lead to the most bias if not addressed properly is __________.
- All missing data
- MAR
- MCAR
- NMAR
The NMAR (Not Missing at Random) missing data mechanism could lead to the most bias if not addressed properly as the missingness is related to the unobserved data.
If a distribution is bimodal with two distinct peaks, there may be _____ distinct mode(s).
- None
- One
- Three
- Two
In a bimodal distribution, there are "Two" distinct modes or peaks. Hence, there may be two distinct modes.
You are conducting a study on the annual rainfall in various cities. The data recorded is in millimeters. What type of data is this?
- Continuous data
- Discrete data
- Nominal data
- Ordinal data
Rainfall measurement in millimeters is a continuous variable because it can take on any value within a range.