A Practical Approach to Timeseries Forecasting Using Python - Time Series Parameters

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Computers
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9th - 10th Grade
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Hard
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary purpose of calculating correlation in a dataset?
To identify the maximum value in a dataset
To find the average of all values
To determine the relationship between different features
To calculate the total sum of all columns
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How can you calculate the correlation between two specific columns in a dataframe?
By using the max function
By updating the command with specific column names
By writing df.corr()
By using the sum function
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does a positive correlation indicate about two columns?
One column is always greater than the other
They have a similar trend
They have no data
They are completely unrelated
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does MAP stand for in data analysis?
Mean Absolute Percentage Error
Maximum Average Percentage
Minimum Absolute Percentage
Mean Average Precision
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which library is used to calculate MAP and MAE in Python?
sklearn
Matplotlib
Pandas
NumPy
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main difference between MAE and RMSE?
MAE is a percentage, RMSE is a square root
MAE measures average error, RMSE measures squared error
MAE is for time series, RMSE is for static data
MAE is more accurate than RMSE
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the final step in calculating RMSE?
Summing all the errors
Calculating the mean of all errors
Dividing the total error by the number of observations
Taking the square root of the mean squared error
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