| Day |
Subject matter |
Homework assignment |
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| CHAPTER 1: DATA
COLLECTION |
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| Day 1 |
1.1 Intro to the
Practice of Statistics |
Ex. 1.1 #13 - 36 All |
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| 1.3 Simple Random
Sampling |
Ex. 1.3 #12a (Use Table
1, Col 4 & 5, Start at Row 3) |
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| 1.5 Bias in Sampling |
Ex. 1.5 #13 - 18 All |
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| CHAPTER 2:
ORGANIZING & SUMMARIZING DATA |
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| Day 1 cont'd. |
2.1 Organizing
Qualitative Data |
Ex. 2.1 #18 (Parts a
thru e) |
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| 2.2 Organizing
Quantitative Data |
Ex. 2.2 #41 (Omit part
d) |
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| 2.3 Graphical
Misrepresentation |
Ex. 2.3 #14 |
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| CHAPTER 3:
NUMERICALLY SUMMARIZING DATA |
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| Day 2 |
3.1 Measures of Central
Tendency |
Ex. 3.1 #17, 18, 23,
24, 31 |
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| 3.2 Measures of
Dispersion |
Ex. 3.2 #11 &
12 (Use definition formula, show work) #24 & 25 (Use your calculator) |
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| Day 3 |
3.3 Using Grouped Data | Ex. 3.3 #13 |
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| 3.4 Measures of
Position & Outliers |
Ex. 3.4 #12, 15, 16, 22 |
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| 3.5 Five-No. Summary
& Boxplots |
Ex. 3.5 #5, 6, 10 |
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| CHAPTER 4:
DESCRIBING THE RELATION BETWEEN TWO VARIABLES |
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| Day 4 |
4.1 Scatter Diagrams
& Correlation |
Ex. 4.1 #9 - 14
All, #20 (Use definition formula given Sx
= 3.56 and Sy = 2.55) Also #23 all parts, use your calculator to find r. |
|
| 4.2 Least Squares
Regression |
Ex. 4.2 #9, 10,
21 (Note that #21 uses the scatter plot from #23 in Section 4.1) |
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| CHAPTER 5:
PROBABILITY |
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| Day 5 |
5.1 Probability Rules | Ex. 5.1 #13 - 16
All, #25 - 34 All |
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| 5.2 The Addition Rule
& Complements |
Ex. 5.2 #5 - 20
All, #25, 32 |
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| Day 6 |
5.4 Conditional
Probability |
Ex. 5.4 #3 - 9
All, #18, 36 |
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| 5.5 Counting Techniques |
Ex. 5.5 #6 - 39 Mx3
(multiples of 3) Also, #45, 48, 51 |
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| Day 7 |
Review |
No written HW, study for
midterm |
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| Day 8 |
Midterm #1 |
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| CHAPTER 6:
DISCRETE PROBABILITY DISTRIBUTIONS |
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| 8cntd. | 6.1 Discrete Random Variables | Ex. 6.1 #7, 8, 13, 14,
15, #19 (Show steps for E(X), omit parts d & e), Also #28 |
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| Day 9 |
6.2 The Binomial
Probability Distribution |
Ex. 6.2 #7 - 14
All, #17, 21, #32 (But with n=5 and, in part b, compute the mean only) Also, #35 Parts a & b only |
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| CHAPTER 7: THE
NORMAL PROBABILITY DISTRIBUTION |
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| Day
10 |
7.1 Properties of the
Normal Distribution 7.2 The Standard Normal (z) Distribution 7.3 Applications of the Normal Distribution |
Ex. 7.1 #7 - 12
All, #18 - 28 All Ex. 7.2 #9, 11, 15, 19, 25, 27, 33 Ex. 7.3 #17, 18 |
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| CHAPTER 8:
SAMPLING DISTRIBUTIONS |
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| Day 11 |
8.1
Distribution
of the Sample Mean 8.2 Distribution of the Sample Proportion |
Ex.
8.1 #11, 12, 17, 18, 23, 24 Ex. 8.2 #7, 8, 11, 12, 16, 21, 23 |
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| Day 12 |
Review |
No written HW, study for
midterm |
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| Day 13 |
Midterm #2 |
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| CHAPTER 9:
ESTIMATING PARAMETERS USING CONFIDENCE INTERVALS |
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| 13cont | 9.1 Estimate Mean When Population SD is known | Ex. 9.1 #13, 14, 17,
18, 21, 22, 47, 48 |
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| Day 14 |
9.2 Estimate Mean When
Population SD is not known 9.3 Confidence Intervals for a Population Proportion |
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| CHAPTER 10:
HYPOTHESIS TESTS REGARDING A PARAMETER |
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| Day 15 |
10.1 The Language of
Hypothesis Testing |
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| Day 16 |
10.2 Test for Mean when
Population SD is known 10.3 Test for Mean when Population SD is unknown |
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| CHAPTER 11:
INFERENCES ON TWO SAMPLES |
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| Day
17 |
11.1 Inference RE
Means: Dependent Samples 11.2 Inference RE Means: Independent Samples |
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| CHAPTER 12:
ADDITIONAL INFERENTIAL PROCEDURES |
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| Day 18 | 12.1 Goodness-of-Fit
Test |
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| Day 19 |
12.2 Independence &
Homogeneity Tests |
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| Day 20 |
Review for final |
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