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An infinite population has a standard deviation of 10.  A random sample of 100 items from this population is selected.  The sample mean is determined to be 60.  At 98% confidence, the margin of error is

		1.28
		1.645
		1.96
		2.33
		None of the above

The z value for a 90% confidence interval estimation is

		1.28
		1.645
		1.96
		2.33
		2.576

The t value for a 90% confidence interval estimation with 24 degrees of freedom (not the sample size n) is

		1.317836
		1.710882
		2.063899
		2.492159
		2.796939

A random sample of 144 observations has a mean of 20, a median of 21, and a mode of 22.  The population standard deviation is known to equal 3.6.  The 90% confidence interval for the population mean is

		19.62 to 20.38
		19.51 to 20.49
		19.41 to 20.59
		19.30 to 20.70

A random sample of 144 observations has a mean of 20, a median of 21, and a mode of 22, and a standard deviation of 3.6..  The 90% confidence interval for the population mean is

		19.60 to 20.40
		19.48 to 20.52
		19.33 to 20.67
		18.20 to 20.80

A random sample of 64 students at a university showed an average age of 20 years and a sample standard deviation of 4 years.  The 90% confidence interval for the true average age of all students in the university is

		19.58 to 20.42
		19.35 to 20.65
		19.15 to 20.85
		19.00 to 21.00

The following random sample from a population whose values were normally distributed was collected.  

10

15

11

12

              The 95% confidence interval for μ is

		11.00 to 13.00
		10.23 to 13.77
		9.46 to 14.54
		8.56 to 15.44

For a two-tailed Z-test at a 0.05 level of significance; the table (critical) value

		-1.96 and 1.96
		-1.645 and 1.645
		-2.33 and 2.33
		-2.575 and 2.575

For a one-tailed Z-test at a 0.10 level of significance; the table (critical) value

		-1.96 and 1.96
		-1.645 and 1.645
		-1.28 and 1.28
		-2.575 and 2.575

n = 36	H0: 20
= 22	Ha: > 20
= 12

               The test statistic equals

		1.30
		1.00
		-1.30
		1.50

n = 36	H0: ≥ 20
= 18	Ha: < 20
= 6

               The p-value equals

		0.1587
		0.0668
		0.0228
		0.0107

n = 36	H0: ≥20
= 18	Ha: < 20
= 12

               If the test is done at a .05 level of significance, the null hypothesis should

		not be rejected
		be rejected
		Not enough information is given to answer this question.
		None of the other answers are correct.

n = 9	H0: = 50
= 48	Ha: 50

s = 3 Assume data are from normal population

           The p-value is equal to

		0.0171
		0.0805
		0.2705
		0.2304

n = 36	H0: 20
= 22	Ha: > 20
s = 6

               The p-value equals

		0.0267
		0.0403
		0.1621
		0.1733
= 36	H0: μ ≥ 20
= 18	Ha: μ < 20
s = 6

               If the test is done at a .05 level of significance, the null hypothesis should

		not be rejected
		be rejected
		Not enough information is given to answer this question.
		None of the other answers are correct.

n = 9	H0: = 50
= 53	Ha: 50

= 3 Assume data are from normal population

           The p-value is equal to

		0.0455
		0.0027
		0.2703
		0.3173

A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation    = 50,000 − 8x   The above equation implies that an

		increase of $1 in price is associated with a decrease of $8 in sales
		increase of $8 in price is associated with an increase of $8,000 in sales
		increase of $1 in price is associated with a decrease of $42,000 in sales
		increase of $1 in price is associated with a decrease of $8000 in sales

In a regression analysis if SSE = 500 and SSR = 300, then the coefficient of determination is

		0.6000
		0.1666
		1.6666
		0.3750

Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable).  

x	y
2	12
3	9
6	8
7	7
8	6
7	5
9	2

The least squares estimate of b0 equals

		-0.7647
		-0.1125
		13.75
		16.412

Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable).  

x	y
2	12
3	9
6	8
7	7
8	6
7	5
9	2

The coefficient of determination equals

		0.7705
		-0.9941
		0.9941
		0.8438

Below you are given a partial computer output based on a sample of fifteen (15) observations.       

	ANOVA
		df	SS
	Regression	1	50.58
	Residual
	Total	14	106.00
		Coefficients	Standard Error	t Stat    p-value
	Intercept	16.156	1.42	0.0000
	Variable x	-0.903	0.26	0.0000

  The estimated regression equation (also known as regression line fit) is

		Y = 0 + 1X1  + ε,
		E(Y) = 0 + 1X1 + 2X2
		Ŷ = -0.903 + 16.156X1
		Ŷ = 16.156 - 0.903X1
		none of the above

Below you are given a partial computer output based on a sample of fifteen (15) observations.       

	ANOVA
		df	SS
	Regression	1	50.58
	Residual
	Total	14	106.00
		Coefficients	Standard Error	t-stat	p-value
	Intercept	16.156	1.42		0.0000
	Variable x	-0.903	0.26		0.0000

  To test whether the parameter 1 is significantly different from zero (i.e., Ha: β1 ≠ 0), the calculated test statistic equals

		2.0619
		-1.628
		-3.473
		11.377
		none of the above

Below you are given a partial computer output based on a sample of fifteen (15) observations.       

	ANOVA
		df	SS
	Regression	1	50.58
	Residual
	Total	14	106.00
		Coefficients	Standard Error	t Stat	p-value
	Intercept	16.156	1.42		0.0000
	Variable x	-0.903	0.26		0.0000

  To test whether the parameter 1 is significantly different from zero (i.e., Ha: β1 ≠ 0) at 10% significance level, the critical value (table value) for the test is

		2.571
		2.160
		2.015
		1.771
		none of the above

Below you are given a partial computer output based on a sample of fifteen (15) observations.       

	ANOVA
		df	SS
	Regression	1	50.58
	Residual
	Total	14	106.00
		Coefficients	Standard Error	t Stat	p-value
	Intercept	16.156	1.42		0.0000
	Variable x	-0.903	0.26		0.0000

  To test whether the parameter 1 is significantly different from zero (i.e., Ha: β1 ≠ 0) at 10% significance level, we will conclude to

		reject H0 and conclude β1 = 0
		reject H0 and conclude β1 ≠ 0
		fail to reject H0 and conclude β1 = 0
		fail to reject H0 and conclude β1 ≠ 0
		none of the above

Below you are given a partial computer output based on a sample of fifteen (15) observations.       

	ANOVA
		df	SS
	Regression	1	50.58
	Residual
	Total	14	106.00
		Coefficients	Standard Error	t Stat	p-value
	Intercept	16.156	1.42		0.0000
	Variable x	-0.903	0.26		0.0000

          The coefficient of determination is.

		0.5228
		0.4772
		0.6535
		0.3465