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Stats help starts here.

Statistics Problem Index

Frustrated with a particular MyStatLab/MyMathLab homework problem?  No worries!  Just use the ID # located towards the top left of your assignment window to find the help you need in the table below.  Each topic title links to a video showing you step by step how to solve the problem.  Watch each video as often as you want.  The help here is free!

Don't see your problem ID # in the list below?  You can go to the Contact page and submit a request.  The homework problem with the most votes from independent users (only one vote per user will be counted) gets posted first.  You can also peruse through problem solving videos on our blog to see if a similar homework problem has been worked.

Total # of problems worked here, on YouTube, and in the online Stat 101 course = Hundreds!

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ID #

Topic

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Introduction to FREE Stat 101 course resources
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Finding a specific Stat 101 Homework Help video
1.1.15
Distinguishing between statistical and practical significance for a gender selection study
1.1.30
Calculating and comparing an exact value with a practical value
1.2.26
Determining the appropriate level of measurement for Olympic years
1.2.32
Identifying the level of measurement for a movie rating
1.3.6
Distinguishing an observational study from an experiment
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2.1.16
Constructing a frequency distribution table with a specified class width
2.1.19
Constructing a relative frequency distribution from a frequency counts table in Excel
2.1.19
Constructing a relative frequency distribution from a frequency counts table in StatCrunch
2.2.6
Identifying the class width in a histogram
2.2.13
Constructing a histogram from a frequency distribution table
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2.3.7
Constructing a stem-and-leaf plot
2.3.12
Constructing a Pareto chart from a frequency distribution table
2.3.15
Constructing a frequency polygon in StatCrunch
2.4.9
Identifying a critical R-value
2.4.10
Identifying and interpreting critical R-values
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3.1.17
Finding the mean, median, mode, midrange, and outliers of a data set
3.1.29
Finding the mean of a frequency distribution
3.2.10
Finding and interpreting measures of variation
3.2.22
Finding the coefficient of variation for parking meters
3.2.26-T
Finding measures of variation before and after adding a data point
3.2.41
Using the Empirical Rule to derive proportions
3.2.43
Use Chebyshev's Theorem to derive proportions
3.3.9
Converting z-scores into real-world values in StatCrunch
3.3.17
Finding percentiles in a data set
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4.1.22
Finding the probability of a false positive drug test from tabulated data
4.1.42
Finding the probability of winning at roulette
4.2.11
Finding probability from a frequency table and identifying disjoint events
4.2.13
Finding probability from a frequency table for selections with and without replacement
4.2.27
Finding the probability of accepting a batch in manufacturing
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4.3.15
Find conditional probability from a frequency table
4.3.19
Finding the positive predictive value of a polygraph test
4.4.23
Finding probabilities using permutations and combinations
4.4.28
Finding the number of possible selections from more than enough candidates
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5.1.7
Finding the mean and standard deviation for a probability distribution
5.1.16
Using the Range Rule of Thumb to find significant values
5.2.13
Finding probability using the multiplication rule
5.2.26
Finding a binomial distribution probability of "no more than"
5.2.33-T
Finding a binomial distribution probability for a combined test sample
5.2.36-T
Using a binomial distribution to evaluate toy manufacturing quality control
5.3.14-T
Using the Poisson distribution to evaluate malignant tumor data
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6.1.8
Finding a uniform distribution probability using StatCrunch
6.1.14-T
Finding a z score for a standard normal distribution using StatCrunch
6.1.38-T
Finding the percentile for a standard normal distribution
6.2.7
Finding the area under a normal distribution curve using StatCrunch
6.2.26-T
Finding percentiles using a normal distribution
6.2.31
Using a nonstandard normal distribution to evaluate pregnancy and premature birth data
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6.3.7
Creating a variance sampling distribution probability distribution table
6.3.9
Creating in StatCrunch a probability distribution table for a sampling distribution of the medians
6.4.6-T
Finding probabilities for different sample sizes using a nonstandard normal distribution
6.4.18-T
Applying a nonstandard normal distribution to boat design
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6.5.9-T
Creating and interpreting a normal quantile plot
6.5.17-T
Creating a normal quantile plot to find z-scores
6.6.16-T
Finding and interpreting the probability of flu side effects from a cholesterol treatment
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7.1.33-T
Finding the sample size needed to estimate a mean confidence interval of student completion rates
7.1.37-T
Finding the sample size needed to estimate a population proportion
7.2.1
Finding a confidence interval given summary sample data
7.2.13-T
Finding and interpret a confidence interval for a population mean (σ unknown)
7.2.29-T
Finding the sample size needed to estimate a confidence interval on a population mean
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7.3.5-T
Finding degrees of freedom, critical values, and a standard deviation confidence interval estimate
7.3.11-T
Finding and interpreting a confidence interval for a population standard deviation
7.4.13-T
Using bootstrap methods to construct a proportion confidence interval estimate
7.4.19-T
Using bootstrap methods to construct a mean confidence interval estimate
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8.1.8
Identifying the symbolic claim and hypotheses for a claim about a population standard deviation
8.1.13
Finding the value of the test statistic for hypothesis testing on proportions
8.1.19
Using a z-score to complete hypothesis testing for a claim of inequality
8.2.5
Using a calculator display to perform hypothesis testing on proportions
8.2.19-T
Using StatCrunch to perform hypothesis testing on the proportion of polygraph results
8.2.31-T
Using StatCrunch to perform hypothesis testing on proportions of jury selections
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8.3.5-T
Finding the P-value given the test statistic
8.3.13-T
Using StatCrunch to perform hypothesis testing on means of course evaluation scores
8.3.25-T
Using StatCrunch to perform hypothesis testing on means of female pulse rates
8.4.9-T
Performing hypothesis testing on standard deviations of piston diameters in StatCrunch
8.4.13-T
Using StatCrunch to perform hypothesis testing on standard deviations of aircraft altimeters
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9.1.10-T
Using StatCrunch to perform hypothesis testing on two proportions of referee calls
9.1.13-T
Performing hypothesis testing on two proportions in StatCrunch
9.2.5-T
Performing hypothesis testing on two independent sample means of soda can fill volumes
9.2.10-T
Using StatCrunch to perform hypothesis testing on two independent sample means of body temperatures
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9.3.5-T
Using StatCrunch to perform hypothesis testing on two matched pair means of acting award ages
9.3.13-T
Using StatCrunch to construct a confidence interval for two matched pair means of hospital admissions
9.4.5-T
Performing hypothesis testing on the variances of skull measurements
9.4.7-T
Using StatCrunch to perform hypothesis testing on two standard deviations of alcohol treatments
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10.1.10
Performing correlation hypothesis testing
10.1.12-T
Evaluating the correlation of data values that produce box patterns
10.2.10-T
Using StatCrunch to find a regression line equation
10.2.13
Finding the regression equation and best predicted value for bear chest size
10.2.34-T
Finding the regression equation and best predicted value for earthquake data
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10.3.9
Finding the linear correlation coefficient from a Minitab display
10.3.17-T
Finding the explained variation, the unexplained variation, and a prediction interval estimate
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10.4.12
Finding the best predicted value using the best multiple regression model
10.4.13-T
Finding the best regression equation given multiple variables
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10.5.7-T
Finding the best nonlinear regression model for a subway fare
10.5.15-T
Finding the best nonlinear regression model for stock market index values
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11.1.13-T
Applying goodness of fit hypothesis testing to horse race post positions
11.1.21-T
Using goodness of fit and Benford's Law for hypothesis testing to detect check fraud
11.2.18-E
Performing contingency table hypothesis testing to evaluate baseball player birthdays
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12.1.11-T
Applying one-way ANOVA hypothesis testing to bicycle lap times
12.1.18-E
Using one-way ANOVA for hypothesis testing and the Bonferroni test
12.2.4
Recognizing a balanced design in two-way ANOVA hypothesis testing
12.2.11
Recognizing the effect of data transformations on two-way ANOVA results
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13.2.8-T
Performing a sign hypothesis test of median heights
13.4.6-T
Performing the Wilcoxon signed ranks test for earnings by education
13.5.7-T
Performing the Kruskal-Wallis test for chest deceleration measurements
13.6.8-T
Performing Spearman's rank correlation test for audience impressions
13.7.5-T
Performing the runs test for randomness in law enforcement fatalities using StatCrunch
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