MA07 Forecasting
Quiz
•
Other
•
University
•
Hard

Ting Irenda
Used 8+ times
FREE Resource
7 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
30 sec • 5 pts
What is the key difference between a FORECAST vs a BUDGET?
A budget is an estimate of what will happen in the future.
A forecast is a plan of the utilization of the company's resources in the future.
A forecast is a detailed representation of the company's plan for the future.
A budget is a plan of the utilisation of the company's resources in the future.
2.
MULTIPLE CHOICE QUESTION
30 sec • 5 pts
The key difference between the excel function FORECAST and REGRESSION function is
FORECAST Function can have more than one independent variables.
FORECAST Function can have more than one dependent variables.
REGRESSION function can have more than one independent variables.
REGRESSION function can have more than one dependent variables.
3.
MULTIPLE CHOICE QUESTION
20 sec • 5 pts
In the formula Y = m1 X1 + m2 X2 + C,
m1 and m2 are termed as ______
independent variables
dependent variables
coefficients
intercept
4.
MULTIPLE CHOICE QUESTION
30 sec • 5 pts
In the formula Y = m1 X1 + m2 X2 + C,
X1 and X2 are termed as ______
Independent Variables
Dependent Variables
Intercept
Coefficients
5.
MULTIPLE CHOICE QUESTION
30 sec • 5 pts
Regression Formula:
Module Grades = (m1 x Study Time) - (m2 x Social Media time) + C
Which of the following statement is true of the above Regression formula?
Module Grades is the Independent Variable.
Study Time and Social Media time are the Dependent Variables
The higher the Social Media time the lower the Module Grade.
If Study Time and Social Media Time are 0, then Module Grade is 0.
6.
MULTIPLE CHOICE QUESTION
30 sec • 5 pts
The Hong Kong government has predicted that in the next month, there's a possibility of 30% of Grade 1 typhoon, and 60% of a tropical storm.
What is the probability that it will be a light rain?
10%
100%
60%
30%
7.
MULTIPLE CHOICE QUESTION
30 sec • 5 pts
In a Regression Analysis, R2 = 0.97 refers to ______.
the observed dependent variables are extremely scattered around the regression equation
the observed independent variables are closely aligned to the regression equation.
the observed independent variables are extremely scattered around the regression equation.
the observed independent variables are a perfect fit to the regression equation.
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