A Practical Approach to Timeseries Forecasting Using Python - Autoregression

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Computers
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10th - 12th 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 does the term 'order' in auto regression refer to?
The number of future values predicted
The number of preceding inputs used
The number of variables in the model
The number of coefficients in the model
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does the parameter 'P' affect the auto regression model?
It determines the number of future predictions
It sets the number of past values considered
It specifies the number of coefficients used
It defines the number of variables in the model
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
If 'P' is set to 3, which past values are used for prediction?
t-2, t-3, t-4
t-1, t-3, t-4
t-1, t-2, t-3
t-1, t-2, t-4
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the milk distribution example, what is calculated to determine significant lags?
PACF values
Time series averages
ACF values
Regression coefficients
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the significance of a PACF value being above a threshold?
It shows a model error
It signifies a significant lag for analysis
It represents a constant value
It indicates a future prediction
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which module is used to implement auto regression in Python?
matplotlib
statsmodels
pandas
numpy
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of the TQDM module in the Python implementation?
To show progress of the algorithm
To import data
To evaluate algorithms
To visualize data
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