As MSUB students you should have access to their academic support center for the purpose of getting help with you course in times during which I am unavailable. At last posting, it would seem that you need to download the outlined app and make an appointment in order to receive online support. If you are seeking help, and need an extension on homework, please let me know so that I can make accommodations, as well.
Chapter 2:
Section 2.1, pgs. 37-41: #2.5, 2.7, 2.11, 2.15, 2.18, 2.20
Section 2.2, pgs. 49-52: #2.35, 2.37, 2.42
Section 2.3, pgs. 61-65: #2.61, 2.64, 2.68, 2.72
Section 2.4, pgs. 69-70: #2.85, 2.87 (calculate variance by hand), 2.92
Section 2.5, pgs. 76-78: #2.100, 2.102, 2.109
Section 2.6, pg. 82: #2.122, 2.124
Chapter 3:
Section 3.1, pgs. 129-132:#3.11, 3.12, 3.17, 3.32, 3.36
Sections 3.2-3.4, pgs. 140-144: #3.45, 3.46, 3.51, 3.53, 3.55, 3.57, 3.61, 3.64, 3.65, 3.66
Sections 3.5-3.6, pgs. 154-158: #3.76, 3.78, 3.82, 3.87, 3.88, 3.90, 3.96, 3.100, 3.101
***After our conversation about Galileo's Passe-Dix game, I found this description of much of the solution. Although it would seem there may be more, this website gives a sufficient solution until I am able to put together a more comprehensive one.
Problem 2.15: The graph that you can use to complete the problem is given at the bottom of the page, but if you would like to use the StatCrunch feature to analyze the data, note the following ice type numbers: Type 1 is First-Year, Type 2 is Multi-Year, and Type 3 is Landfast.
In addition to the digital practice exam that you have access to through Stat Lab, you will want to study the following concepts/problems to prepare for the paper exam:
Constructing and interpreting histograms (See Example 2.2 on pages 46-47)
Calculate mean, median, and standard deviation for a small data set (See Example 2.3 on page 54, Example 2.5 on page 56, and Example 2.9 on page 67)
Apply Chebyshev's and/or the Empirical Rule to interpret aspects of a data set, including z-scores (See Example 2.11 on pages 72-73, Example 2.13 on pages 74-75, and Example 2.15 on pages 80-81)
Calculate probabilities using a two-way data table and rules of probability (See Example 3.5 on pages 125-126, Example 3.9 on pages 134-135, Example 3.14 on pages 145-146, Example 3.19 on page 151)
Chapter 4:
Section 4.1, pg. 188: #4.3, 4.8, 4.10, 4.13, 4.15
Section 4.2, pgs. 192-196: #4.20, 4.23, 4.25, 4.29, 4.31, 4.32, 4.39
Section 4.3, pgs. 199-201: #4.44 (calculate by hand), 4.50, 4.55
Section 4.4, pgs. 211-214: #4.59, 4.62, 4.64, 4.69, 4.74, 4.81, 4.83
Chapter 5:
Sections 5.1 & 5.2, pgs. 237-239: #5.3, 5.4, 5.5, 5.6, 5.9, 5.11, 5.14, 5.17, 5.20
Section 5.3, pgs. 250-253: #5.26, 5.28, 5.32, 5.33, 5.36, 5.37, 5.43, 5.44, 5.46, 5.50, 5.53
Section 5.4, pgs. 258-261: #5.62, 5.64, 5.67, 5.70
In addition to the digital practice exam that you have access to through Stat Lab, you will want to study the following concepts/problems to prepare for the paper exam:
Determine the expected value (mean) and standard deviation for discrete random variables
Determine the expected value (mean) and standard deviation for binomial random variables
Determine the probability density function, mean, standard deviation, and probabilities of events for a continuous random variable that has a uniform probability distribution
Determine the probability of an event for a continuous random variable with a normal distribution and/or determine the boundary for a probability by converting the distribution to the standard normal.
Chapter 6:
Section 6.1, pgs. 290-291: #6.3, 6.5, 6.9
Section 6.2, pgs. 294-295: #6.14, 6.16, 6.19
Section 6.3, pgs. 301-304: #6.27, 6.30, 6.37, 6.38, 6.44, 6.48
Chapter 7:
Sections 7.1 & 7.2, pgs. 322-326: #7.7, 7.8, 7.9, 7.11, 7.13, 7.16, 7.21, 7.27
Section 7.3, pgs. 333-336: #7.32, 7.34, 7.38, 7.40, 7.45, 7.49
Section 7.4, pgs. 341-344: #7.55, 7.58, 7.61, 7.62, 7.65, 7.71, 7.72
Section 7.5, pgs. 348-350: #7.77, 7.79, 7.82, 7.84, 7.86, 7.91, 7.93, 7.95
Chapter 8:
Sections 8.1 & 8.2, pgs. 379-380: #8.8, 8.9, 8.12, 8.13, 8.16, 8.18, 8.20
Section 8.3, pg. 384: #8.22 - 8.25, 8.29, 8.30
Section 8.4, pgs. 389-393: #8.33, 8.348.38, 8.40, 8.44, 8.48
Section 8.5, pgs. 397-400: #8.53, 8.54, 8.56, 8.58, 8.60, 8.67
Section 8.6, pgs. 405-408: #8.76, 8.77, 8.81, 8.84, 8.90
In addition to the digital practice exam that you have access to through Stat Lab, you will want to study the following concepts/problems to prepare for the paper exam:
Given sample size, population mean, and population standard deviation, determine the standard error of the mean for the sample, and the probability that any sample will have a mean within a particular range. (See Examples 6.8 & 6.9 on pages 298-299).
Determine a large-sample confidence interval for a population proportion, evaluating the validity of the sample, using Wilson's adjustment if necessary, and making a qualitative statement about the meaning of the confidence interval as it relates to all possible sample means. (See Examples 7.7 & 7.8 on pages 339-341)
Determine the sample size needed to achieve a particular sampling error with a given confidence level when given the population standard deviation. (See Examples 7.9 and 7.10 on pages 346-348)
Use the Student's t-Statistic to conduct a two-tailed hypothesis test on the mean when given a population mean, sample mean, sample standard deviation, sample size and confidence level. You will need to specify either the rejection region or the p-value in order to justify your choice of whether to reject the null hypothesis. (See the text discussion on pages 393-394)
Chapter 9:
Sections 9.1-9.2, pgs. 447-453: #9.6, 9.9, 9.11, 9.12, 9.16, 9.24, 9.25
Section 9.3, pgs. 460-465: #9.35-9.37, 9.41, 9.44, 9.47, 9.53
Section 9.5, pgs. 476-477: #9.81, 9.82, 9.85, 9.88, 9.91
Chapter 11:
Sections 11.1, pgs. 589-590: #11.7, 11.11, 11.13, 11.14
Section 11.2, pgs. 597-603: #11.18, 11.19, 11.21, 11.22, 11.23, 11.25, 11.27, 11.33
Section 11.3, pgs. 606-608: #11.38, 11.39, 11.40, 11.42, 11.43, 11.45, 11.46, 11.51
Section 11.5, pgs. 623-627: #11.82, 11.83, 11.87, 11.90, 11.92, 11.95, 11.98
In addition to the digital practice exam that you have access to through Stat Lab, you will want to study the following concepts/problems to prepare for the paper exam:
Given a scenario determine whether or not an independent-sample or a paired-difference experiment should be used to conduct a small-sample hypothesis test, and use corresponding t-values to confirm your choice. (Focus on Chapter 9, Section 3)
Determine the size of sample needed for a large-sample scenario to achieve a particular sampling error given a confidence level and standard deviation. (See Example 9.8 on pages 473-474)
Formulate a least squares regression line when given values of B_0 and B_1, describe the relationship between the variables using these values, and use the line to predict a dependent value when given an independent value. Use the probabilistic model to explain the amount of difference between the actual and predicted value. (See Example 11.2 on pages 592-594)
Calculate and use the coefficient of determination to draw conclusions about the relationship between two variables, and compare relationships for different groups. (Use Example 11.6 on page 622)
Here is the table of values corresponding to areas under the standard normal curve between the mean and a particular positive z-value.
Table of Areas Under the Standard Normal Curve
Here is the table of critical values for working with the student's t-statistic.
Critical Values for Student's t-Statistic
100people.org is a website devoted to bringing global issues and statistics about different parts of the world into light. It is a great source for some simple statistics and studies.
Gapminder is a non-profit organization devoted to debunking common myths about other countries and parts of the world in general. Part of their website includes a tool for graphing/animating/displaying data in "4 dimensions".
The Canvas of Babel - Opening Line: "There is a website, right now, that contains a photo of your funeral." This may be the best opening line to a YouTube video that I have ever seen. The video talks about a couple of achievements of humanity that have fascinating implications, and could lead to some very interesting questions of probability. For example: "If I were to view a random image in the archive every second for the rest of my life, what is the chance that I would see a picture of myself riding a narwhal with Scarlett Johansson and a t-rex over a rainbow with a backdrop of Gene Simmons of Kiss performing at Madison Square Garden for the very last time on December 2, 2023?" Whether the event occurs or not, that image is in there...