Psychology
Denene Rice
1.In conceptual terms, the hypothesis is that social exclusion increases belief in fake news. State the null and research hypotheses in statistical terms.
The mean belief score in the treatment groups equals that in the control group,
Null- H0: u t= u c
The mean belief score in the treatment group is greater than that in the control group,
Research- H1: M t > M c
2.Explain why the t-test for independent samples is appropriate to test the hypothesis in terms of the formula for t.
The numerator of t computes the difference between the means for the treatment and control groups. The denominator considers the exactness of this distinction by considering changeability and test size.
3.Using SPSS, compute the t statistic, as well as the means and standard deviations of each group.
M t= 4.6, SD= 2.3. Mc=3.2, SD=1.7, t=1.07, df=8, p=.314
4.Compute and interpret the effect size, d, for the differences between means, indicating if it is small, medium, or large.
The effect size is 0.69 which is a medium effect size
5.Summarize the results of the t-test, including the correct notation. Is t statistically significant? Should you reject or retain the null hypothesis? What is the probability of a type 1 error?
The difference between the means is not statistically significant, t (8) =1.07, p>.05, more than .05. Maintain the null given the elevated risk of a type 1 error, p=.314
6.Is the difference between the means likely to be found in the population? why or why not?
No, the difference between the means in the sample was found by error, and occurred by chance, therefore it is not likely to be found in the population.
7.Is the difference between the means likely to be meaningful? why or why not?
Yes, the difference in the sample is likely to be meaningful, as indicated by ES, a medium effect size, but is not likely to be found in the populations, as indicated by t.
Denene Rice
1.
In conceptual terms, the hypothesis is that social exclusion increases belief in fake news. State
the null and research hypotheses in statistical terms.
The mean belief score in the treatment groups equals that in the control group,
Null
-
H0: u t= u c
Th
e mean belief score in the treatment group is greater than that in the control group,
Research
-
H1: M t > M c
2.
Explain why the t
-
test for independent samples is appropriate to test the hypothesis in terms of
the formula for t.
The numerator of t
computes
the
difference
between the me
ans
for the treatment and control
g
roups
. The denominator considers the
exactness of this distinction by considering changeability
and test size.
3.
Using SPSS, c
ompute the t statistic, as well as the means and standard deviations of eac
h
group.
M
t= 4
.
6, SD= 2.3. Mc=3.2
,
SD=1.7
, t
=1.07, df=8, p=.314
4.
Compute and interpret the effect size, d, for the differences between means, indicating if it is
small,
medium,
or large.
The effect size is
0.69
which
is a mediu
m effect size
5.
Summarize the results of the t
-
test, including the correct
notation.
Is t statistically
significant?
Should you reject or retain the null hypothesis? What is the probability of a type 1
error?
The difference between the means is not statistically significant,
t (
8) =
1.07, p>.05,
more
than .05.
Maintain
the null given
the
elevated
risk of a type 1 error, p=.314
6.
Is the difference between the means likely to be found in the
population? why or why not?
No, the difference between the means in the sample was found by error, and occurred
by chance, therefore it is not likely to be found in the population.
Denene Rice
1.In conceptual terms, the hypothesis is that social exclusion increases belief in fake news. State
the null and research hypotheses in statistical terms.
The mean belief score in the treatment groups equals that in the control group,
Null- H0: u t= u c
The mean belief score in the treatment group is greater than that in the control group,
Research- H1: M t > M c
2.Explain why the t-test for independent samples is appropriate to test the hypothesis in terms of
the formula for t.
The numerator of t computes the difference between the means for the treatment and control
groups. The denominator considers the exactness of this distinction by considering changeability
and test size.
3.Using SPSS, compute the t statistic, as well as the means and standard deviations of each
group.
M t= 4.6, SD= 2.3. Mc=3.2, SD=1.7, t=1.07, df=8, p=.314
4.Compute and interpret the effect size, d, for the differences between means, indicating if it is
small, medium, or large.
The effect size is 0.69 which is a medium effect size
5.Summarize the results of the t-test, including the correct notation. Is t statistically
significant? Should you reject or retain the null hypothesis? What is the probability of a type 1
error?
The difference between the means is not statistically significant, t (8) =1.07, p>.05,
more than .05. Maintain the null given the elevated risk of a type 1 error, p=.314
6.Is the difference between the means likely to be found in the population? why or why not?
No, the difference between the means in the sample was found by error, and occurred
by chance, therefore it is not likely to be found in the population.