問題一覧
1
_____________ is a statistical method used to determine whether a relationship between variables exist.
Correlation
2
A ____________ is sometimes written as one-word, scatterplot is also called scatter graph or scatter diagram.
scatter plot
3
A _____________ shows how each point collected from a set of bivariate data are scattered on the Cartesian plane, it gives a good visual picture of the ____ variables which helps in finding the relationship that exists between the two variables.
scatter plot, two
4
A ______________ is a graphical representation of the relationship between two variables.
scatter plot
5
_______________ is a useful tool for checking the assumptions in a regression analysis
scatter diagram
6
Scatter diagram is a useful tool for checking the assumptions in a ___________ analysis
regression
7
It can be viewed during an initial screening run of the analysis or after the analysis.
Scatterplot
8
Scatter plot can be viewed during an ________ screening run of the analysis or _______ the analysis.
initial, after
9
The benefit of looking at scatter diagram residuals in the ____________ stages of an analysis is that it may save a researcher time.
beginning
10
Scatter plot :
If the assumptions are _____ met, further screening must be applied ___________ the analysis can be completed and data may require cleansing and transformation.
not, before
11
In this case, the researcher is not running analysis haphazardly. For instance, the assumptions are met, the regression is ready to be run and the researcher has ____________ confidence that the chances of making a Type I or Type II error are _________ ultimately improving the accuracy of any research results.
increased, reduced
12
The direction of correlation maybe __________, ___________or ______
positive, negative, zero
13
A __________ correlation exists when high values of one variable correspond to high values in the other variable or low values in one variable correspond to low values in the other variable
positive
14
A positive correlation exists when _____ values of one variable correspond to ______ values in the other variable or _____ values in one variable correspond to ____ values in the other variable.
high, high, low, low
15
A __________ correlation exists when high values in one variable correspond to low values in the other variable or low values in one variable correspond to high values in theother variable.
negative
16
A negative correlation exists when _____ values in one variable correspond to _____ values in the other variable or ____ values in one variable correspond to _____ values in theother variable.
high, low, low, high
17
A ______ correlation exists when high values in one variable correspond to either high or low values in the other variable.
zero
18
A zero correlation exists when high values in one variable correspond to _______ high or low values in the other variable.
either
19
The strength of correction may be ________, very high, moderately high, moderately low, very low and zero.
perfect
20
Pearson product-moment correlation is the most widely used in statistics to measure the degree of the relationship between the _________ related variables.
linear
21
__________ product-moment correlation is the most widely used in statistics to measure the degree of the relationship between the linear related variables.
Pearson
22
The ___________ correlation would require both variables to be normally distributed.
Pearson r
23
__________ refers to the departure of two random variables from independence.
Correlation
24
The Pearson r correlation would require _____ variables to be normally distributed. Correlation refers to the departure of ____ random variables from _____________.
both, two, independence
25
__________ correlation is used to measure the degree of relationship between the two products.
Pearson r
26
The ___________ is defined as the covariance divided by the standard deviations of the variables
correlation coefficient
27
The correlation coefficient is defined as the covariance ________ by the standard deviations of the variables.
divided
28
Pearson’s product-moment correlation coefficient or simply correlation coefficient (or _____________) is a measure of the ________ strength of the association between ___ variables.
Pearson's r, linear, two
29
It is founded by Karl Pearson.
Pearson's r
30
The value of the correlation coefficient varies between ____ and _____. When the value of the correlation coefficient lies around _____ then it is said to be a perfect degree of association between the two variables.
-1, +1, ±1, perfect
31
As the value of the correlation coefficient goes closer to ______ the relationship between the two variables will be _______
zero, weaker
32
no correlation, no relationship
0.00
33
very low correlation, almost negligible relationship
±0.01 - ±0.20
34
slight correlation, definite but small relationship
±.0.21-±0.40
35
moderate correlation, substantial relationship
±0.41-±0.70
36
high correlation, marked relationship
±0.71-±0.90
37
very high correlation, very dependable relationship
±0.91-±0.99
38
perfect correlation, perfect relationship
1.00
39
The test for correlation coefficient is ______-tailed; the __________ region is divided into ____ equal parts
two, rejection, two
40
The test of ___________ is two-tailed; the rejection region is divided into two equal parts
correlation
Topic 1
Topic 1
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Topic 1
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Topic 2 : Inflation
Mikyii · 59問 · 1年前Topic 2 : Inflation
Topic 2 : Inflation
59問 • 1年前問題一覧
1
_____________ is a statistical method used to determine whether a relationship between variables exist.
Correlation
2
A ____________ is sometimes written as one-word, scatterplot is also called scatter graph or scatter diagram.
scatter plot
3
A _____________ shows how each point collected from a set of bivariate data are scattered on the Cartesian plane, it gives a good visual picture of the ____ variables which helps in finding the relationship that exists between the two variables.
scatter plot, two
4
A ______________ is a graphical representation of the relationship between two variables.
scatter plot
5
_______________ is a useful tool for checking the assumptions in a regression analysis
scatter diagram
6
Scatter diagram is a useful tool for checking the assumptions in a ___________ analysis
regression
7
It can be viewed during an initial screening run of the analysis or after the analysis.
Scatterplot
8
Scatter plot can be viewed during an ________ screening run of the analysis or _______ the analysis.
initial, after
9
The benefit of looking at scatter diagram residuals in the ____________ stages of an analysis is that it may save a researcher time.
beginning
10
Scatter plot :
If the assumptions are _____ met, further screening must be applied ___________ the analysis can be completed and data may require cleansing and transformation.
not, before
11
In this case, the researcher is not running analysis haphazardly. For instance, the assumptions are met, the regression is ready to be run and the researcher has ____________ confidence that the chances of making a Type I or Type II error are _________ ultimately improving the accuracy of any research results.
increased, reduced
12
The direction of correlation maybe __________, ___________or ______
positive, negative, zero
13
A __________ correlation exists when high values of one variable correspond to high values in the other variable or low values in one variable correspond to low values in the other variable
positive
14
A positive correlation exists when _____ values of one variable correspond to ______ values in the other variable or _____ values in one variable correspond to ____ values in the other variable.
high, high, low, low
15
A __________ correlation exists when high values in one variable correspond to low values in the other variable or low values in one variable correspond to high values in theother variable.
negative
16
A negative correlation exists when _____ values in one variable correspond to _____ values in the other variable or ____ values in one variable correspond to _____ values in theother variable.
high, low, low, high
17
A ______ correlation exists when high values in one variable correspond to either high or low values in the other variable.
zero
18
A zero correlation exists when high values in one variable correspond to _______ high or low values in the other variable.
either
19
The strength of correction may be ________, very high, moderately high, moderately low, very low and zero.
perfect
20
Pearson product-moment correlation is the most widely used in statistics to measure the degree of the relationship between the _________ related variables.
linear
21
__________ product-moment correlation is the most widely used in statistics to measure the degree of the relationship between the linear related variables.
Pearson
22
The ___________ correlation would require both variables to be normally distributed.
Pearson r
23
__________ refers to the departure of two random variables from independence.
Correlation
24
The Pearson r correlation would require _____ variables to be normally distributed. Correlation refers to the departure of ____ random variables from _____________.
both, two, independence
25
__________ correlation is used to measure the degree of relationship between the two products.
Pearson r
26
The ___________ is defined as the covariance divided by the standard deviations of the variables
correlation coefficient
27
The correlation coefficient is defined as the covariance ________ by the standard deviations of the variables.
divided
28
Pearson’s product-moment correlation coefficient or simply correlation coefficient (or _____________) is a measure of the ________ strength of the association between ___ variables.
Pearson's r, linear, two
29
It is founded by Karl Pearson.
Pearson's r
30
The value of the correlation coefficient varies between ____ and _____. When the value of the correlation coefficient lies around _____ then it is said to be a perfect degree of association between the two variables.
-1, +1, ±1, perfect
31
As the value of the correlation coefficient goes closer to ______ the relationship between the two variables will be _______
zero, weaker
32
no correlation, no relationship
0.00
33
very low correlation, almost negligible relationship
±0.01 - ±0.20
34
slight correlation, definite but small relationship
±.0.21-±0.40
35
moderate correlation, substantial relationship
±0.41-±0.70
36
high correlation, marked relationship
±0.71-±0.90
37
very high correlation, very dependable relationship
±0.91-±0.99
38
perfect correlation, perfect relationship
1.00
39
The test for correlation coefficient is ______-tailed; the __________ region is divided into ____ equal parts
two, rejection, two
40
The test of ___________ is two-tailed; the rejection region is divided into two equal parts
correlation