REM B LVL 1 Flashcards

1
Q

In Advanced Mathematics, it converts a
discrete-time signal, which is a
sequence of real or complex numbers,
into a complex frequency-domain
representation.

A. Z-transform
B. Borel Transform
C. Laplace Transform

A

A. Z-transform

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2
Q

In Advanced Mathematics, it is an
integral transform that converts a
function of a real variable t to a complex
variable s.

A. Laplace Transform
B. Borel Transform
C. Fourier Transform
D. Z-transform

A

A. Laplace Transform

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3
Q

If a power series has a positive radius of convergence and sum that is identically zero throughout its interval of
convergence, then each coefficient of
the series must be

A. Negative
B. Zero
C. One

A

B. Zero

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4
Q

Which of the following statements
describes the sequence

(REM MATH B LVL 1 FIGURE)

A. The sequence is monotonic.
B. The sequence if unbounded.
C. The sequence is bounded.
D. The sequence converges to a number less
than 1.

A

C. The sequence is bounded.

As n increases, the value of an =(0.5,0.866,1,0.866,0.5,0,-0.5, -0.866,-1,-0.5, 0,0.5,0.866, 1…).
Thus, the sequence is divergent, is not
monotone and bounded.

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5
Q

Indicate the nature of the second order
equation

(REM MATH B LVL 1 FIGURE)

A. Parabolic differential equation
B. Hyperbolic differential equation
C. Elliptic differential equation

A

A. Parabolic differential equation

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6
Q

Determine the nature of the second
order equation

(REM MATH B LVL 1 FIGURE)

A. Hyperbolic differential equation
B. Elliptic differential equation
C. None of these
D. Parabolic differential equation

A

A. Hyperbolic differential equation

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7
Q

The PDE A d^2 u/dx^2 + B d^2 u/dxdy +
C d^2 u/dy^2 +D= 0 is hyperbolic if.

A. B^2-4AC=0
B. B^2-4AC>0
C. B^2-4AC<0

A

B. B^2-4AC>0

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8
Q

___ is one of the
mathematical equations for an
indefinite function of one or more than one variables that relate the values of the function. Differentiation of an equation in various orders.

A. Simultaneous Differential equation
B. Heat equation
C. Bessel’s differential equation
D. Legendre’s Polynomial

A

A. Simultaneous Differential equation

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9
Q

It is also known as characteristic vector of a linear transformation is a nonzero vector that changes at most by a scalar factor when that linear transformation is applied to it, often denoted by 入.

A. Eigenvector
B. Gauss-Jordan Elimination
C. Matrix Inversion

A

A. Eigenvector

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10
Q

It is the sum of the area of each
rectangle within a given interval under
the curve of a function.

A. Lagrange Theorem
B. Trapezoidal Rule
C. Simpson’s Rule
D. Midpoint Rule

A

D. Midpoint Rule

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11
Q

The approximation of the derivative at x:
f’(x)=(f(x+h)-f(x))/h; is called

A. Forward differencing
B. Centered differencing
C. Backward differencing
D. Both Forward differencing and Centered
differencing

A

A. Forward differencing

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12
Q

The approximation of the derivative at x:
f’(x)=(f(x+h)-f(x-h))/2h; is called

A. Both Forward differencing and Centered
differencing
B. Forward differencing
C. Centered differencing
D. Backward differencing

A

C. Centered differencing

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13
Q

Which of the following numerical
methods is more accurate in evaluating
definite integral

A. Lagrange Theorem
B. Midpoint Rule
C. Trapezoidal Rule
D. Simpson’s Rule

A

D. Simpson’s Rule

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14
Q

The approximation of the derivative of x:
f’(x)=(f(x)-f(x-h))/h; is called.

A. Forward differencing
B. Backward differencing
C. Both Forward differencing and Centered
differencing

A

B. Backward differencing

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15
Q

Approximation of the value of definite
integral by using trapezoids rather than
rectangles.

A. Midpoint Rule
B. Trapezoidal Rule
C. Lagrange Theorem

A

B. Trapezoidal Rule

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16
Q

What are external data sources for
analysis?

A. Data obtained from public databases
and third parties
B. Data collected from customer surveys
C. Data generated and collected within your
organization

A

A. Data obtained from public databases
and third parties

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17
Q

It divides the data into 100 equal
regions.

A. Decile
B. Inter-Quartile Range
C. Percentile
D. Population

A

C. Percentile

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18
Q

Which of the following external data
sources can provide insights into
consumer sentiment and social
behavior?

A. Production records
B. Social media platforms
C. Employee performance data

A

B. Social media platforms

Social media platforms generate usergenerated content that can be analyzed to gain insights into consumer
sentiment, public opinion, trends, and
social behavior.

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19
Q

What is the characteristic of first-party
data collected from customer surveys?

A. It is available in government portals
B. It is purchased from third-party
organizations
C. It is unstructured and unreliable
D. It is directly collected by the company
from customers

A

D. It is directly collected by the company
from customers

First-party data collected from
customer surveys is a form of data
directly collected by the company from
its customers. It is structured and
provides valuable insights into
customer preferences, opinions, and
experiences.

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20
Q

What type of interview provides the
greatest flexibility?

A. Structured interviews
B. Unstructured interviews
C. Semi-structured interviews
D. Comparative interviews

A

B. Unstructured interviews

Unstructured interviews provide the
greatest flexibility, as there are no
predetermined questions. The
conversation flows naturally, allowing
participants to share their perspectives and provide insights on various aspects related to the topic.

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21
Q

A study in which a sample is used to make an interference to a conceptual (future) population.

A. Analytic Study
B. Retrospective Study
C. Enumerative Study
D. Observational Study

A

A. Analytic Study

Analytic Study - a sample is used to make an
interference to a conceptual (future) population.

Enumerative Study - a sample is used to make an interference to the population from which the sample is selected.

Retrospective Study - uses either all of a sample of the historical process data archived over some period of time.

Observational Study - a person observes the process or population, disturbing it as little possible,and records the quantities of interest.

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22
Q

What type of data can be found in
academic research publications?

A. Data collected through experiments,
surveys, or simulations
B. Financial ratios and indicators
C. Manufacturing data and production logs

A

A. Data collected through experiments,
surveys, or simulations

Academic research publications provide
access to data collected through
experiments, surveys, simulations, or
observational studies relevant to
specific fields.

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23
Q

One in which every member of the
population has an equal likelihood of
appearing.

A. Random Sample
B. Sample
C. Probability

A

A. Random Sample

Probability is an area of study which involves predicting the relative likelihood of various outcomes.

A sample is a chosen part of the
population in question.
Statistics is a collection of numbers.

A random sample is one in which every member of the population has an equal likelihood of appearing

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24
Q

Data analysis is the process of:

A. Collecting data from various sources
B. Presenting data in visual charts and
graphs.
C. Manipulating and exploring data to
extract meaningful insights.

A

C. Manipulating and exploring data to
extract meaningful insights.

Data analysis involves manipulating and
exploring data to extract meaningful
insights, draw conclusions, and support decision-making. It includes techniques such as statistical analysis, regression analysis, neural networks, and text
analysis.

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25
Q

It divides the data into 10 equal regions.

A. Population
B. Decile
C. Percentile

A

B. Decile

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26
Q

What is one of the key tasks in data
cleaning?

A. Aggregating data from numerous sources
B. Identifying major gaps in the data
C. Extracting irrelevant data points

A

C. Extracting irrelevant data points

One of the key tasks in data cleaning is
to remove irrelevant data points that
have no bearing on the intended
analysis. This helps to streamline the dataset and focus only on the relevant observations for accurate analysis.

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27
Q

It is the mean of the squares of the
deviations of each measurement from
the mean of the population.

A. Interquartile Range
B. Variance
C. Standard Deviation

A

B. Variance

The interquartile range is the difference between the upper quartile and the lower quartile.

One simple measure of variability is the
sample range, the difference between the smallest item and the largest item in each sample.

Variance is the mean of the squares of the deviations of each measurement from the mean of the population.

Standard deviation is defined as the square
root of the variance.

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28
Q

It represents the average of the sample
population.

A. Mode
B. Quantile
C. Median
D. Mean

A

D. Mean

Mode is the value which appears most
frequently.

Median divides a sample of data in a way that 50% of the values are smaller than the median and 50% of values are bigger (or equal).

Mean represents the average of the sample
population.

Quantile is a value that divides the sample into
two parts.

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29
Q

What role does data analysis play in
decision-making?

A. Data analysis supports decision-
making based on evidence.
B. Data analysis ensures data accuracy and
reliability.
C. Data analysis collects data for reference.

A

A. Data analysis supports decision-
making based on evidence.

Data analysis supports decision-making
by providing evidence-based insights
and actionable information. It helps
make informed decisions and supports
identifying areas for improvement.

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30
Q

An area of study which involves
predicting the relative likelihood of
various outcomes.

A. Probability
B. Random Sample
C. Sample

A

A. Probability

Probability is an area of study which involves predicting the relative likelihood of various outcomes.

A sample is a chosen part of the
population in question.

Statistics is a collection of numbers.

A random sample is one in which every member of the population has an equal likelihood of appearing.

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31
Q

A study which uses either all of a
sample of the historical process data
archived over some period of time.

A. Analytic Study
B. Retrospective Study
C. Observational Study

A

B. Retrospective Study

Analytic Study - a sample is used to make an
interference to a conceptual (future) population.

Enumerative Study - a sample is used to make an interference to the population from which the sample is selected.

Retrospective Study - uses either all of a sample of the historical process data archived over some period of time.

Observational Study - a person observes the process or population, disturbing it as little possible,and records the quantities of interest.

32
Q

It is the difference between the smallest
item and the largest item in each
sample.

A. Sample Range
B. Variance
C. Interquartile Range
D. Standard Deviation

A

A. Sample Range

The interquartile range is the difference between the upper quartile and the lower quartile.

One simple measure of variability is the sample range, the difference between the smallest item and the largest item in each sample.

Variance is the mean of the squares of the deviations of each measurement from the mean of the population.

Standard deviation is defined as the square
root of the variance.

33
Q

What is the first step in the data
analysis process?

A. Analyzing the data
B. Drawing conclusions
C. Collecting data
D. Defining the objective

A

D. Defining the objective

The first step in the data analysis
process is to define the objective or
problem statement. This involves
formulating a hypothesis and
understanding the business problem
that needs to be solved.

34
Q

A study in which a person observes the process or population, disturbing it as little possible, and records the quantities of interest.

A. Enumerative Study
B. Analytic Study
C. Observational Study

A

C. Observational Study

Enumerative Study - a sample is used to make an interference to the population from which the sample is selected.

Retrospective Study - uses either all of a sample of the historical process data archived over some period of time.

Observational Study - a person observes the process or population, disturbing it as little possible,and records the quantities of interest.

35
Q

A value that divides the sample into two
parts.

A. Mode
B. Mean
C. Median
D. Quantile

A

D. Quantile

36
Q

Where does second-party data come
from?

A. It is the first-party data of other
organizations
B. It is obtained from government portals and
open data repositories
C. It is collected by the company from its
customers

A

A. It is the first-party data of other
organizations

Second-party data refers to the first-
party data of other organizations. It can be obtained directly from the company or through a private marketplace.
Examples include website activity, app usage, social media activity, purchase histories, and shipping data.

37
Q

Which of the following is an example of
a data collection method?

A. Surveys
B. Hypothesis testing
C. Literature review

A

A. Surveys

Surveys are a common data collection
method used to gather information from respondents through a set of structured questions.

38
Q

It is the value which appears most
frequently.

A. Quantile
B. Mean
C. Mode

A

C. Mode

39
Q

Which of the following is an example of
an internal data source in engineering
data analysis?

A. Production records
B. Industry reports
C. Government publications
D. Public databases

A

A. Production records

Production records are generated and collected within the organization and provide insights into the efficiency,
output, and quality of manufacturing or
production operations

40
Q

What does skewness measure in the
context of statistics?

A. The symmetry of data distribution
B. The relationship between two variables
C. The peakness of data distribution

A

A. The symmetry of data distribution

Skewness measures the asymmetry of
a data distribution. A positive skew
indicates a tail on the right side, a
negative skew indicates a tail on the left
side.

41
Q

What does the mean of a distribution
represent?

A. The center of the distribution
B. The shape of the distribution
C. The probability of an event occurring
D. The spread of the data

A

A. The center of the distribution

The mean of a distribution represents the central location around which the data is clustered.

42
Q

What is a parameter in statistics?

A. A characteristic or attribute that can take
on different values
B. A range of values that likely contains the
true population parameter
C. A numerical characteristic of a
population
D. A numerical characteristic calculated from
a sample

A

C. A numerical characteristic of a
population

Parameters are numerical
characteristics that describe the
population as a whole, such as the
average, proportion, or standard
deviation of a certain measurement in
the population.

43
Q

Which of the following questions is a
statistical question?

A. How many hours of professional training
took place over the weekend?
B. How many professional sports leagues
are there?
C. Where do the professional sports leagues
play?
D. How many hours do the student-athletes at your school spend each week training for a sports league?

A

B. How many professional sports leagues
are there?

A statistical question is a question that can be answered by collecting data that vary. In the given options, how many
professional sports leagues are there?is a statistical question. Here to answer this question, we have to collect data
from the sources.

44
Q

The probability of rejecting a true
hypothesis is called

A. Test statistics
B. Statement of hypothesis
C. Level of significance

A

C. Level of significance

The probability of rejecting a true
hypothesis is called the level of
significance. The level of significance,also known as alpha (a), represents the maximum acceptable probability of
making a Type I error, which is rejecting
a true null hypothesis. It is typically set
before conducting a hypothesis test and
helps determine the critical region of
the test.

45
Q

In hypothesis testing, a critical value is
used to

A. Assess the significance of the
statistical test
B. Set the research hypothesis
C. Accept the null hypothesis
D. Determine the sample size

A

A. Assess the significance of the
statistical test

A critical value is used to compare the
test statistic and determine whether the
obtained result is statistically
significant. It helps in deciding whether
to reject or accept the null hypothesis.

46
Q

Which test we normally apply for
Qualitative data?

A. X Chi-square test
B. Z-test
C. T-test
D. F-test

A

A. X Chi-square test

X Chi-square test is a statistical
hypothesis test that compares two
variables of a contingency test to check
how they are related. It is a
nonparametric test and this test
normally applies to qualitative data.

47
Q

The rejection probability of Null
Hypothesis when it is true is called as

A. Level of Rejection
B. Level of Margin
C. Level of Confidence
D. Level of Significance

A

D. Level of Significance

The probability of committing a type l
error (rejecting the null hypothesis when it is actually true) is called a (alpha) the other name for this is the level of
statistical significance.

48
Q

Statistical significance alone does not
provide information about the

A. Population size
B. Sample size
C. Confidence interval
D. Effect size

A

D. Effect size

Statistical significance only indicates whether the observed effect is likely to have occurred by chance or not. It does not provide information about the
magnitude or importance of the effect.

49
Q

What is a type I error in hypothesis
testing?

A. Accepting the alternative hypothesis when
it is false
B. Rejecting the null hypothesis when it is
true
C. Accepting the null hypothesis when it is
true
D. Failing to reject the null hypothesis when it
is false

A

B. Rejecting the null hypothesis when it is
true

A type I error (false-positive) occurs if an investigator rejects a null hypothesis that is actually true in the population; a type Il error (false-negative) occurs if
the investigator fails to reject a null
hypothesis that is actually false in the
population.

50
Q

Rejection of the null hypothesis is a conclusive proof that the alternative hypothesis is

A. False
B. True
C. Neither
D. Either

A

C. Neither

The rejection of the null hypothesis in
favor of the alternative hypothesis
cannot be taken as conclusive proof that the alternative hypothesis is true,but rather as a piece of evidence that
increases one’s belief in the truth of the
alternative hypothesis.

51
Q

A statement whose validity is tested on
the basis of a sample is called

A. Composite Hypothesis
B. Null Hypothesis
C. Statistical Hypothesis
D. Simple Hypothesis

A

C. Statistical Hypothesis

In testing of Hypothesis, a statement
whose validity is tested on the basis of
a sample is called as Statistical
Hypothesis. Its validity is tested with
respect to a sample.

52
Q

What is the critical region in hypothesis
testing?

A. The region where the test statistic falls to
reject the null hypothesis
B. The region of acceptance for the
alternative hypothesis
C. The region of rejection for the null
hypothesis

A

C. The region of rejection for the null
hypothesis

A critical region, also known as the
rejection region, is a set of values for
the test statistic for which the null
hypothesis is rejected. i.e. if the
observed test statistic is in the critical
region then we reject the null hypothesis
and accept the alternative hypothesis.

53
Q

If the Critical region is evenly distributed
then the test is referred as

A. Zero tailed
B. One tailed
C. Three tailed
D. Two tailed

A

D. Two tailed

In hypothesis testing, a critical region is a range of values or a set of outcomes that leads to the rejection of the null
hypothesis. It represents the extreme values of the test statistic that would provide evidence against the null hypothesis.

A two-tailed test, also known as a twosided test, is a type of hypothesis test where the critical region is divided
equally on both sides of the distribution.It is used when we want to determine if the sample data significantly deviates from the null hypothesis in either
direction. Therefore, when the critical region is evenly distributed, the test is referred to as a two-tailed test because it considers deviations from the null
hypothesis in both the positive and
negative directions.

54
Q

Goodness of fit of a distribution is
tested by

A. T-test
B. Z-test
C. Chi-square test

A

C. Chi-square test

The goodness of fit test is a statistical hypothesis test to see how well sample data fit a distribution from a population with a normal distribution. There are
multiple types of goodness-of-fit tests,but the most common is the chi-square test. The chi-square test determines if a relationship exists between categorical data. The Kolmogorov-Smirnov test
determines whether a sample comes
from a specific distribution of a
population.

55
Q

The p-value in hypothesis testing
represents

A. The probability of accepting the null
hypothesis when it is true
B. The probability of rejecting the null
hypothesis when it is true
C. The probability of committing a Type I error
D. The probability of obtaining the
observed sample data or more extreme results, assuming the null hypothesis is true

A

D. The probability of obtaining the
observed sample data or more extreme results, assuming the null hypothesis is true

The P value, or calculated probability, is the probability of finding the observed,or more extreme, results when the null hypothesis (H 0) of a study question is true - the definition of ‘extreme’ depends on how the hypothesis is being tested.

56
Q

Which of the following is defined as the
rule or formula to test a Null
Hypothesis?

A. Variance statistic
B. Population statistic
C. Null statistic
D. Test statistic

A

D. Test statistic

57
Q

The alternative hypothesis represents

A. The research hypothesis
B. No effect or no difference
C. The null hypothesis

A

A. The research hypothesis

The alternative hypothesis represents
the researcher’s belief or expectation of
the presence of a relationship or
difference between variables or groups.

58
Q

A probability value is used to assess the

A. Significance of the null hypothesis
B. Critical value
C. Research hypothesis
D. Sample size

A

D. Sample size

A probability value, also known as a p-
value, is used to assess the significance
of the statistical test. It indicates the
probability of obtaining the observed
data or more extreme results assuming
the null hypothesis is true.

59
Q

The coefficient of correlation measures the

A. Sample size
B. Effect size
C. Confidence interval

A

B. Effect size

The coefficient of correlation quantifies the strength of the relationship between two variables. It provides information
about the effect size, indicating how
strong or weak the correlation is.

60
Q

In a hypothesis test, the alternative
hypothesis

A. Is always accepted
B. Represents the status quo
C. Is the opposite of the null hypothesis

A

C. Is the opposite of the null hypothesis

The alternative hypothesis is one of two
mutually exclusive hypotheses in a
hypothesis test. The alternative
hypothesis states that a population parameter does not equal a specified value. The alternative hypothesis represents what we hope to prove or
find evidence for, and it is the opposite
of the null hypothesis.

61
Q

A Type Il error occurs when

A. The null hypothesis is incorrectly
accepted
B. The null hypothesis is incorrectly rejected
C. The null hypothesis is correctly accepted
D. The null hypothesis is correctly rejected

A

A. The null hypothesis is incorrectly
accepted

A type I error (false-positive) occurs if an investigator rejects a null hypothesis that is actually true in the population; a type l error (false-negative) occurs if
the investigator fails to reject a null
hypothesis that is actually false in the
population. Thus, the type Il error occurs
when the null hypothesis is incorrectly
accepted, indicating no effect or
difference when there actually is one.

62
Q

In hypothesis testing, what is the null
hypothesis?

A. The hypothesis that is assumed to be false
B. The hypothesis that is proven to be true
C. The hypothesis that is tested using a two
sample t-test
D. The hypothesis that is based on expert
opinion

A

B. The hypothesis that is proven to be true

The null hypothesis is a statement
assumed to be false or no effect
present, which is tested against an
alternative hypothesis.

63
Q

What is a single-sample hypothesis
testing problem?

A. Testing the hypothesis about the
difference between the sample mean
and a known value.
B. Testing the hypothesis about the
difference between two sample means.
C. Testing the hypothesis about the
difference between two population means.

A

A. Testing the hypothesis about the
difference between the sample mean
and a known value.

In a single-sample hypothesis testing problem, the hypothesis is about the difference between the sample mean and a known or predicted value

64
Q

A statement made about a population
for testing purpose is called

A. Level of Significance
B. Hypothesis
C. Statistic

A

B. Hypothesis

Hypothesis is a statement made about a population in general. It is then tested and correspondingly accepted if True
and rejected if False.

65
Q

Which term refers to the variable being
predicted or explained in regression
analysis?

A. Response variable
B. Error term
C. Independent variable

A

A. Response variable

The response variable, also known as
the dependent variable or outcome
variable, is the variable being predicted or explained in a regression analysis.It is denoted as Y.

66
Q

What does RMSE stand for in regression
analysis?

A. Residual Mean Squared Error
B. Regression Model Standard Error
C. Relative Mean Squared Error
D. Root Mean Squared Error

A

D. Root Mean Squared Error

RMSE stands for Root Mean Squared
Error. It is a measure of the average
difference between the observed and
predicted values of the dependent
variable. RMSE is used to assess the goodness of fit of a regression model,with lower values indicating better fit.

67
Q

Which correlation coefficient assumes a
linear relationship between two
continuous variables?

A. Kendall’s rank correlation coefficient
B. Pearson correlation coefficient
C. Spearman’s rank correlation coefficient
D. Coefficient of determination

A

B. Pearson correlation coefficient

Most often, the term correlation is used
in the context of a linear relationship
between 2 continuous variables and
expressed as Pearson product-moment
correlation. The Pearson correlation
coefficient is typically used for jointly
normally distributed data (data that
follow a bivariate normal distribution)

68
Q

What would be the slopes of two
regression lines parallel to each other?

A. Negative
B. Zero
C. Positive
D. Same

A

D. Same

When two regression lines are parallel to each other, it means that they have the same slope. The slope of a
regression line represents the rate of
change in the dependent variable (Y) for
every unit change in the independent
variable (X). If two regression lines have
different slopes, they would not be
parallel. This would imply that the rate
of change in the dependent variable
differs for each unit change in the
independent variable, leading to lines
that do not run parallel to each other.

69
Q

Which of the following are types of
correlation?

A. Simple, Partial and Multiple
B. All of these choices
C. Linear and Nonlinear
D. Positive and Negative

A

B. All of these choices

70
Q

All data points falling along a straight
line is called

A. Nonlinear relationship
B. Linear relationship
C. Residual
D. Scatter diagram

A

B. Linear relationship

All data points falling along a straight
line is called a linear relationship. A
linear relationship (also known as a
linear association) is a statistical term
that refers to a relationship between
two variables that follows a straight
line.

71
Q

The correlation coefficient describes

A. Only magnitude
B. Only direction
C. Both magnitude and direction
D. None of these choices

A

C. Both magnitude and direction

The correlation coefficient quantifies
the strength and direction of the
relationship between two variables. It
provides information about both the
magnitude (strength) and the direction
of the correlation. The coefficient’s
value indicates how closely the
variables are related and whether the
relationship is positive or negative.

72
Q

Diana placed three tomato plants (A, B,C) under three different types of light.She measured the height of each plant after 3 weeks. What is the dependent variable?

A. The tomato plants
B. The different types of light
C. The height of each plant

A

C. The height of each plant

In an experiment, the dependent
variable is the variable that is measured
or observed and is expected to be
influenced by the independent variable.It is the outcome or response variable that researchers are interested in
studying or understanding.
In this scenario, Diana placed three
tomato plants (A, B, C) under three
different types of light and measured the height of each plant after 3 weeks The dependent variable in this
experiment is the “height of each plant.”It is the variable that Diana measured or observed to determine if it was
influenced by the independent variable,
which is the different types of light.

73
Q

Which of the following is commonly
referred to as ‘data fishing’?

A. None of these choices
B. Data bagging
C. Data booting

A

A. None of these choices

74
Q

Experimental design methods are not
used in ___

A. In process development
B. Evaluating the process capability
C. To obtain a process that is robust and
insensitive to external sources of variability
D. In process troubleshooting to improve
process performance

A

B. Evaluating the process capability

75
Q

Which key concepts are important in
creating a designed experiment?

A. Hypothesis testing and regression analysis
B. Descriptive statistics and data
visualization
C. Correlation and causation
D. Blocking, randomization, and
replication

A

D. Blocking, randomization, and
replication

Key concepts in creating a designed
experiment include blocking (restricting randomization), randomization (order of trials), and replication (repeating the
complete experimental treatment).

76
Q

The DFSS stands for ___

A. Development for six-sigma
B. Design for six-sigma
C. Degradation for Six-sigma
D. Deleting for smaller standards

A

B. Design for six-sigma

DFSS stands for Design for Six Sigma. It
is a methodology that focuses on
designing new products, processes, or services to meet customer needs and achieve high levels of quality and
performance. DFSS aims to proactively address potential issues and variability during the design stage rather than
relying on post-production
improvements or problem-solving. It
incorporates Six Sigma principles and
tools to optimize the design and ensure that the final product or process meets customer requirements while
minimizing defects and variability.

77
Q

In a comparative experiment, what is
the objective?

A. To compare the mean values of
different variables.
B. To observe and record data without
making deliberate changes.
C. To rely solely on scientific theories for
problem-solving
D. To establish cause-and-effect
relationships.

A

A. To compare the mean values of
different variables.

In a comparative experiment, the
objective is to compare the mean values
of different variables or conditions to
determine if there is a significant
difference between them.