1
ISYE6402 Unit 1 Questions 2025/2026
Exam All Answers and Illustrations
Given
Statistical Estimation refers to:? - 🧠 ANSWER ✔✔Obtaining an approximation of
the parameter of a distribution given the data.
Statistical Inference refers to: - 🧠 ANSWER ✔✔Making statistical statements
about an unknown parameter of a distribution, for example, if it is larger than a
given value.
Time Series can be characterized by:
a)Constant or non-constant variability over time.
b)Constant, linear or non-linear trend over time.
c)Cyclical patterns which may happen at regular or irregular time periods.
d)All of the above. - 🧠 ANSWER ✔✔d) All of the above
Trend in a time series can be estimated using the following approach:
1
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STATEMENT. ALL RIGHTS RESERVED
, 2
a)Using non-parametric regression with time being the predictor if we assume no
given shape to the trend.
b)Using multiple linear regression if we assume a linear or polynomial trend.
c)Using nonlinear regression if we assume a known nonlinear trend up to a set of
unknown parameters.
d) All of the above. - 🧠 ANSWER ✔✔d) All of the above.
Seasonality can be estimated using the following approach:
a)Using parametric regression with time being the predicting variable.
b)Fitting a linear regression model with time entering the model as a linear
predictor.
c)Fitting a linear regression model with seasonality represented by a categorical
variable.
d)None of the above. - 🧠 ANSWER ✔✔c)Fitting a linear regression model with
seasonality represented by a categorical variable.
Which of the statements is true?
a)There are multiple approaches that can be used to estimate the seasonality.
2
COPYRIGHT©NINJANERD 2025/2026. YEAR PUBLISHED 2025. COMPANY REGISTRATION NUMBER: 619652435. TERMS OF USE. PRIVACY
STATEMENT. ALL RIGHTS RESERVED
ISYE6402 Unit 1 Questions 2025/2026
Exam All Answers and Illustrations
Given
Statistical Estimation refers to:? - 🧠 ANSWER ✔✔Obtaining an approximation of
the parameter of a distribution given the data.
Statistical Inference refers to: - 🧠 ANSWER ✔✔Making statistical statements
about an unknown parameter of a distribution, for example, if it is larger than a
given value.
Time Series can be characterized by:
a)Constant or non-constant variability over time.
b)Constant, linear or non-linear trend over time.
c)Cyclical patterns which may happen at regular or irregular time periods.
d)All of the above. - 🧠 ANSWER ✔✔d) All of the above
Trend in a time series can be estimated using the following approach:
1
COPYRIGHT©NINJANERD 2025/2026. YEAR PUBLISHED 2025. COMPANY REGISTRATION NUMBER: 619652435. TERMS OF USE. PRIVACY
STATEMENT. ALL RIGHTS RESERVED
, 2
a)Using non-parametric regression with time being the predictor if we assume no
given shape to the trend.
b)Using multiple linear regression if we assume a linear or polynomial trend.
c)Using nonlinear regression if we assume a known nonlinear trend up to a set of
unknown parameters.
d) All of the above. - 🧠 ANSWER ✔✔d) All of the above.
Seasonality can be estimated using the following approach:
a)Using parametric regression with time being the predicting variable.
b)Fitting a linear regression model with time entering the model as a linear
predictor.
c)Fitting a linear regression model with seasonality represented by a categorical
variable.
d)None of the above. - 🧠 ANSWER ✔✔c)Fitting a linear regression model with
seasonality represented by a categorical variable.
Which of the statements is true?
a)There are multiple approaches that can be used to estimate the seasonality.
2
COPYRIGHT©NINJANERD 2025/2026. YEAR PUBLISHED 2025. COMPANY REGISTRATION NUMBER: 619652435. TERMS OF USE. PRIVACY
STATEMENT. ALL RIGHTS RESERVED
