Question

Given a significant F test, the size of the overall effect can be estimated by using a measure equal to the squared Question options: A. correlation between independent and dependent variables. B. curvilinear correlation between independent and dependent variables. C. t ratio. D. treatment effect.

Answer #1

An F-test is a kind of measurable test that is extremely adaptable. the size of the overall effect can be estimated by using a measure equal to the squared . You can utilize them in a wide assortment of settings. F-tests can assess numerous model terms all the while, which enables them to think about the attacks of various direct models. Conversely, t-tests ratio can assess only one term at once.

so answer is c. t-ratio

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1. Which effect size measure should be used if the researcher
wants to understand how much variability is explained by the
treatment?
Cohen's d
any of these
r-squared
a confidence interval
2.
Which of the follow is NOT an assumption of the independent
samples t-test?
Group of answer choices
The observations within each sample must be independent
The populations from which the samples are drawn must be
normal
The populations from which the samples are drawn must have equal
variances...

The overall significance of a regression model is tested using
the F test. The model is significant if:
The F value is low
Unable to answer due to insufficient information
The slope is lower than the intercept
The R squared value is low
The significance level of the F value is low

1. if a statistically significant difference was found between
two means using an independent-samples t test, which of the
following interpretations would be correct.
A) something over and above sampling error is responsible for
the difference between sample means
B) the difference between two means is meaningful.
C)it is unlikely that something other than error is responsible
for the difference between the sample means.
D) the difference between the two means is due to a large effect
size
2. in...

Given:
Ho: Row effect is not significant
H1: Row effect is significant
Ho: Column effect is not significant
H1: Column effect is significant
Ho: Interaction effect is not significant
H1: interaction effect is significant
#
row
column
X
1
A
M
6
2
A
M
12
3
A
M
6
4
A
F
5
5
A
F
6
6
A
F
5
7
B
M
3
8
B
M
2
9
B
M
3
10
B
F
17
11
B...

An experiment consists of three groups (Treatment Group 1,
Treatment Group 2, Placebo Group). What test was MOST likely
used?
Repeated Measures T-test
Z-test
Single Sample T-test
ANOVA
The population mean difference for a T-test of Independent
Samples is ALWAYS
0
1
equal to the population mean minus the sample mean
can't answer/not enough information
A research study reported a LARGE effect size of .8. What effect
size formula was used?
Scheffe
Cohen's D
Tukey
Correlation
.10
.001
.05
.5

5. Measuring effect size for the repeated-measures
ANOVA
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Question 1- Choose the best option
I-When calculating an F ratio for an ANOVA test, what is
the general pattern?
a. There is no relationship between F ratio and p-value
b. F ratio equal the p-value
c. F ratio is always greater than the p-value
d. In general, the smaller the F ratio the smaller the
p-value.
e. In general, the larger the F ratio the smaller the
p-value.
II-Which of the following tools is not appropriate for
studying the...

If you have 1 group and know the population standard deviation,
which test statistic do you use? Question 20 options:
A) dependent samples T-test
B) 2 independent samples T-test
C) Z-test
D) single group T-test
2) The null hypothesis for the dependent t-test is essentially
the same as Question 14 options:
A) Null hypothesis for a Z-score hypothesis test
B) Null hypothesis for a 1 group t-test
C) Null hypothesis for a two independent groups t- test
D) The effect...

Using the data given below, calculate the linear correlation
between the two variables x and y.
X
0
3
3
1
4
y
1
7
2
5
5
(a)
.794
(b)
.878
(c)
.497
(d) .543
Refer to question 4. Assume you are using a 0.05 level of
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Yes
(b) no
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1. Are there statistically significant differences in family
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RESPONDENTS SEX
N
Mean
Std. Deviation
Std. Error Mean
TOTAL FAMILY
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593
17.31
5.625
.231
FEMALE
697
15.94
6.013
.228
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Levene's Test for
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t-test for Equality of
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