Chapter 08 - Confidence Intervals
Chapter 08
Confidence Intervals
Multiple Choice Questions
15. The t distribution approaches the _ as the sample size _.
A. Binomial, increases
B. Binomial, decreases
C. Z, decreases
D. Z, increases
AACSB: Reflective Think
Chapter 03 - Descriptive Statistics: Numerical Methods
Chapter 03
Descriptive Statistics
Multiple Choice Questions Part 1
11. A(n) _ is a graph of a cumulative distribution.
A. Histogram
B. Scatter plot
C. Ogive plot
D. Pie Chart
AACSB: Reflective Thinkin
Chapter 05 - Discrete Random Variables
Chapter 05
Discrete Random Variables
Multiple Choice Questions
9. If p = .1 and n = 5, then the corresponding binomial distribution is
A. Right skewed
B. Left skewed
C. Symmetric
D. Bimodal
AACSB: Reflective Thinking
Chapter 01 - An Introduction to Business Statistics
Chapter 01
An Introduction to Business Statistics
Multiple Choice Questions
10. Statistical methods help to:
A. Demonstrate the need for improvement
B. Identify ways to make improvements
C. Assess whethe
16.4
571
Properties of Second-Order Designs: CCDs
where n is the total number of observations; that is, n
nf + 2p + n0 . So, a central
composite design with nf factorial points and 2p axial points can be made orthogonal by
appropriate choice of or n0 . Fo
572
Chapter 16
Response Surface Methodology
primary advantage of orthogonal blocking as compared with nonorthogonal blocking is that
an orthogonally blocked design gives the smallest values of Var(Y ), Var(i ), Var(ii ), and
Var(ij ). A second advantage i
574
Chapter 16
Response Surface Methodology
Bread our consists of wheat plus a small number of minor ingredients. Their fourth
experiment was concerned with the effects of three such ingredients (labeled design factors
B, C, and D) on loaf volume. An orth
570
Chapter 16
Response Surface Methodology
of a design, since data are generally collected without knowing in which direction from the
design center the stationary point of the tted surface will be located.
Rotatable Central Composite Designs Suppose we
16.5
A Real Experiment: Flour Production Experiment, Continued
573
If the numbers of center points, n0a and n0f , in the blocks can be chosen to satisfy this
equation, then the design will be rotatable and can be orthogonally blocked. When this is
not pos
16.3
563
Second-Order Designs and Analysis
more, all model parameters are estimable. Otherwise, some aliasing will occur, and some
terms will need to be omitted from the second-order model. A design should include enough
replication, often at the center p
16.3
561
Second-Order Designs and Analysis
in the mean response. In subsequent experiments, the levels of such factors can be chosen
farther apart to guard against the last scenario.
16.3
Second-Order Designs and Analysis
16.3.1
Models and Designs
Second-
562
Chapter 16
Response Surface Methodology
where hats on the parameters denote the least squares estimates. Although it is possible to
obtain explicit formulae for the least squares estimates for any specic design, the formulae
for the quadratic paramete
16.3
565
Second-Order Designs and Analysis
with the linear effects have been added (pooled) together, as have those of the quadratic
effects and those of the interaction (cross product) effects. Sequential, or Type I, sums of
squares are listed for each o
568
Chapter 16
Example 16.3.3
Response Surface Methodology
Acid copper pattern plating experiment, continued
In Example 16.3.2, page 563, a second-order model was tted to data collected from a central
composite design. The experiment was run in order to s
566
Chapter 16
Response Surface Methodology
Before settling on a nal model, we should check the lack of t of the second-order
model. The only replication consisted of two center-point observations with values 4.32 and
2
0.00245, so ssPE 0.00245
4.25. The
16.3
567
Second-Order Designs and Analysis
ii s are negative, then the tted model is concave down and has a maximum at the stationary
point. If all of the ii s are positive, then the tted model is concave up and has a minimum
at the stationary point. If s
16.4
Properties of Second-Order Designs: CCDs
569
so the w1 -axis has not been rotated very far from the A-axis (or x1 -axis). We can verify this
from Figure 16.4 on page 564, which shows the surface contours with axes almost parallel to
the A and B axes.
In-Class Quiz #4 Statistics 2035 2013-14 Section 001 (33412412)
Name:
Student Number:
1.
Suppose the amount spent per customer per visit to a local supermarket is normally distributed with a
mean of $65.12 and standard deviation of $21.45. In a random sam
Hypothesis Testing About when is
unknown (section 9.3)
As we saw in section 8.2, when the standard
deviation of the population, , is unknown,
we use the standard deviation of the sample,
s, in place of and use the t-distribution in
place of the z-distribu
One-sample Hypothesis Testing About the
Population Proportion, p (section 9.4)
Recall from Section 7.3:
p
p
= population proportion of success
= proportion of the entire population
that has the specified attribute
= sample proportion of success
= proporti
Estimating the Population Variance
(section 8.4)
In sections 8.1, and 8.2 we were interested
in estimating the mean, , of a population
However, sometimes in statistical analysis,
the researcher is more interested in the
population variance, 2
As an exampl
Weighted Means and Grouped Data (Section 2.8)
(I)
Weighted Means
In calculating the mean of a population or sample, we sum each measurement and divide
by the number of measurements
that is, each measurement is given the same importance or weight
But some