In calculating SMI - M2) , you typically first need to calculate S(MI - M2) is the value used in the denominator of the t statistic for the independent-measures t test. Suppose you conduct a study using an independent-measures research design, and you intend to use the independent-measures t test to test whether the means of the two independent populations are the same. The following is a table of the information you gather. Fill in any missing values. Sample Size Degrees of Freedom Sample Mean Standard Deviation Sums of Squares Sample 1 ni = 41 df, = 40 ▼ M, = 14.3 S, = 8.2 Ss, = 2,689.6 Sample 2 n2 = 21 df, = 20 M2 = 13.6 Sz = 6.8 SS, = 924.8

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Author:Carter
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Chapter10: Statistics
Section10.4: Distributions Of Data
Problem 19PFA
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In calculating
S(M1 – M2)
, you typically first need to calculate
S(M1 – M2)
is the value used in the denominator of
the t statistic for the independent-measures t test.
Suppose you conduct a study using an independent-measures research design, and you intend to use the independent-measures t test to test whether
the means of the two independent populations are the same. The following is a table of the information you gather. Fill in any missing values.
Sample Size
Degrees of Freedom
Sample Mean
Standard Deviation
Sums of Squares
Sample 1
ni = 41
df, = 40
M1
= 14.3
S1 = 8.2
S1
2,689.6
Sample 2
ną = 21
df2 = 20
M2 = 13.6
S2 = 6.8
S2
= 924.8
The pooled variance for your study is 60.240
(Note: You are being asked for this value to three decimal places, because you will need to use it
in succeeding calculations. For the most accurate results, retain these three decimal places throughout the calculations.)
The estimated standard error of the difference in sample means for your study is 2.083
The t statistic for your independent-measures t test, when the null hypothesis is that the two population means are the same, is 0.34
The degrees of freedom for this t statistic is
60
Transcribed Image Text:In calculating S(M1 – M2) , you typically first need to calculate S(M1 – M2) is the value used in the denominator of the t statistic for the independent-measures t test. Suppose you conduct a study using an independent-measures research design, and you intend to use the independent-measures t test to test whether the means of the two independent populations are the same. The following is a table of the information you gather. Fill in any missing values. Sample Size Degrees of Freedom Sample Mean Standard Deviation Sums of Squares Sample 1 ni = 41 df, = 40 M1 = 14.3 S1 = 8.2 S1 2,689.6 Sample 2 ną = 21 df2 = 20 M2 = 13.6 S2 = 6.8 S2 = 924.8 The pooled variance for your study is 60.240 (Note: You are being asked for this value to three decimal places, because you will need to use it in succeeding calculations. For the most accurate results, retain these three decimal places throughout the calculations.) The estimated standard error of the difference in sample means for your study is 2.083 The t statistic for your independent-measures t test, when the null hypothesis is that the two population means are the same, is 0.34 The degrees of freedom for this t statistic is 60
For the independent-measures t test, which of the following describes the pooled variance (whose symbol is
)?
An estimate of the standard distance between the difference in sample means (M - M2) and the difference in the corresponding
population means (P1 - P2)
The variance across all the data values when both samples are pooled together
The difference between the standard deviations of the two samples
A weighted average of the two sample variances (weighted by the sample sizes)
For the independent-measures t test, which of the following describes the estimated standard error of the difference in sample means (whose symbol
is
S(M1 – M2)
)?
A weighted average of the two sample variances (weighted by the sample sizes)
An estimate of the standard distance between the difference in sample means (M - M2) and the difference in the corresponding
population means (P1 - P2)
The variance across all the data values when both samples are pooled together
The difference between the standard deviations of the two samples
In calculating
S(M1 – M2)
, you typically first need to calculate
S(M1 – M2)
is the value used in the denominator of
the t statistic for the independent-measures t test.
Suppose you conduct a study using an independent-measures research design, and you intend to use the independent-measures t test to test whether
the means of the two independent populations are the same. The following is a table of the information you gather. Fill in any missing values.
Transcribed Image Text:For the independent-measures t test, which of the following describes the pooled variance (whose symbol is )? An estimate of the standard distance between the difference in sample means (M - M2) and the difference in the corresponding population means (P1 - P2) The variance across all the data values when both samples are pooled together The difference between the standard deviations of the two samples A weighted average of the two sample variances (weighted by the sample sizes) For the independent-measures t test, which of the following describes the estimated standard error of the difference in sample means (whose symbol is S(M1 – M2) )? A weighted average of the two sample variances (weighted by the sample sizes) An estimate of the standard distance between the difference in sample means (M - M2) and the difference in the corresponding population means (P1 - P2) The variance across all the data values when both samples are pooled together The difference between the standard deviations of the two samples In calculating S(M1 – M2) , you typically first need to calculate S(M1 – M2) is the value used in the denominator of the t statistic for the independent-measures t test. Suppose you conduct a study using an independent-measures research design, and you intend to use the independent-measures t test to test whether the means of the two independent populations are the same. The following is a table of the information you gather. Fill in any missing values.
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