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Statistics Homework Help 24/7

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Our stats tutors are the best. And, they are online right now, ready to help with everything from correlations to probabilities to permutations. They’ll help you solve tough statistics homework problems, double check your answers and make sure you understand key concepts before the next test. These are just a few of the topics a tutor can help you master:

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Statistics Help for Students

Welcome to StatisticsHelp.org. The main purpose of the site is to provide all kinds of free statistics help resources, in the form of online calculators, graph makers, handouts, tutorials, guides and solved statistics problems.

Online Statistics Calculators and Solvers

See what we have to offer you. Please choose one of the online statistics solvers and other resources that we have available for you.

Statistics Calculators

Check out our useful statistics calculators for normal distributions, confidence intervals and statistical tests.

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Solved Stats Questions

Go through our hundreds of solved stats questions, with detailed solutions.

Statistics Guides

Guides that will show you step by step how to do specific tasks in Statistics.

Tech and Calculators

Reviews of technology and calculators that can help you in your statistics classes.

Interesting news in Statistics and Education in general.

Statistics Help Online

Our site provides a number of online resources, mainly aimed at college students taking basic statistics classes. For this kind of students the normal distribution and the t-distribution will be at the center stage.

And that is why we provide our normal calculators and confidence interval calculators, for both the z-distribution and t-distribution.

Feel free to use all the resources in website that could be of use for you. The resources in this website are intended for you to get some practice for statistics tests or homework, or just some statistical curiosity.

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Statistics Answers

One of the most frequently requested tool is the access to statistics answers. For that reason, our members have worked hard to put out a relatively short list of sample statistics problems, but which are very representative of what you will find on your stats tests or homework, so then it could prove useful to start with those. For that you can check the link below.

We are always trying to improve our stats apps, so we are more than happy to receive suggestions. In fact suggestion are what can make this site better, for the whole community.

Solved Statistics Problems - Practice Exercises

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Statistics Tutors

Many of the members of our community are tutors, so we are working on a way to get community members connected. One way we are thinking about is to start a Stats forum, which is likely come to fruition very soon.

Do not miss our new guide on how to study for your Stats exam or midterm . Find tips and strategies to succeed in your examinations! Also see the differences between descriptive statistics and inferential statistics with some examples.

✔ Do you know the difference between Statistics and Probability ? Check it out!

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AIDS patients.

The average length of time (in months) AIDS patients live after treatment.

X = the length of time (in months) AIDS patients live after treatment

• 823,088 823,856 823,088 823,856
• quantitative discrete
• quantitative continuous
• In both years, underwater earthquakes produced massive tsunamis.

simple random

values for X , such as 3, 4, 11, and so on

No, we do not have enough information to make such a claim.

Take a simple random sample from each group. One way is by assigning a number to each patient and using a random number generator to randomly select patients.

This would be convenience sampling and is not random.

Yes, the sample size of 150 would be large enough to reflect a population of one school.

Even though the specific data support each researcher’s conclusions, the different results suggest that more data need to be collected before the researchers can reach a conclusion.

There is not enough information given to judge if either one is correct or incorrect.

The software program seems to work because the second study shows that more patients improve while using the software than not. Even though the difference is not as large as that in the first study, the results from the second study are likely more reliable and still show improvement.

Yes, because we cannot tell if the improvement was due to the software or the exercise; the data is confounded, and a reliable conclusion cannot be drawn. New studies should be performed.

No, even though the sample is large enough, the fact that the sample consists of volunteers makes it a self-selected sample, which is not reliable.

No, even though the sample is a large portion of the population, two responses are not enough to justify any conclusions. Because the population is so small, it would be better to include everyone in the population to get the most accurate data.

• Inmates may not feel comfortable refusing participation, or may feel obligated to take advantage of the promised benefits. They may not feel truly free to refuse participation.
• Parents can provide consent on behalf of their children, but children are not competent to provide consent for themselves.
• All risks and benefits must be clearly outlined. Study participants must be informed of relevant aspects of the study in order to give appropriate consent.
• all children who take ski or snowboard lessons
• a group of these children
• the population mean age of children who take their first snowboard lesson
• the sample mean age of children who take their first snowboard lesson
• X = the age of one child who takes his or her first ski or snowboard lesson
• values for X , such as 3, 7, and so on
• the clients of the insurance companies
• a group of the clients
• the mean health costs of the clients
• the mean health costs of the sample
• X = the health costs of one client
• values for X , such as 34, 9, 82, and so on
• all the clients of this counselor
• a group of clients of this marriage counselor
• the proportion of all her clients who stay married
• the proportion of the sample of the counselor’s clients who stay married
• X = the number of couples who stay married
• all people (maybe in a certain geographic area, such as the United States)
• a group of the people
• the proportion of all people who will buy the product
• the proportion of the sample who will buy the product
• X = the number of people who will buy it
• buy, not buy

quantitative discrete, 150

qualitative, Oakland A’s

quantitative discrete, 11,234 students

qualitative, Crest

quantitative continuous, 47.3 years

• The survey was conducted using six similar flights. The survey would not be a true representation of the entire population of air travelers. Conducting the survey on a holiday weekend will not produce representative results.
• Conduct the survey during different times of the year. Conduct the survey using flights to and from various locations. Conduct the survey on different days of the week.

Answers will vary. Sample Answer: You could use a systematic sampling method. Stop the tenth person as they leave one of the buildings on campus at 9:50 in the morning. Then stop the tenth person as they leave a different building on campus at 1:50 in the afternoon.

Answers will vary. Sample Answer: Many people will not respond to mail surveys. If they do respond to the surveys, you can’t be sure who is responding. In addition, mailing lists can be incomplete.

convenience cluster stratified systematic simple random

• qualitative

Causality: The fact that two variables are related does not guarantee that one variable is influencing the other. We cannot assume that crime rate impacts education level or that education level impacts crime rate.

Confounding: There are many factors that define a community other than education level and crime rate. Communities with high crime rates and high education levels may have other lurking variables that distinguish them from communities with lower crime rates and lower education levels. Because we cannot isolate these variables of interest, we cannot draw valid conclusions about the connection between education and crime. Possible lurking variables include police expenditures, unemployment levels, region, average age, and size.

• Possible reasons: increased use of caller id, decreased use of landlines, increased use of private numbers, voice mail, privacy managers, hectic nature of personal schedules, decreased willingness to be interviewed
• When a large number of people refuse to participate, then the sample may not have the same characteristics of the population. Perhaps the majority of people willing to participate are doing so because they feel strongly about the subject of the survey.

The sum of the travel times is 1,173.1. Divide the sum by 50 to calculate the mean value: 23.462. Because each state’s travel time was measured to the nearest tenth, round this calculation to the nearest hundredth: 23.46.

Explanatory variable: amount of sleep Response variable: performance measured in assigned tasks Treatments: normal sleep and 27 hours of total sleep deprivation Experimental Units: 19 professional drivers Lurking variables: none – all drivers participated in both treatments Random assignment: treatments were assigned in random order; this eliminated the effect of any “learning” that may take place during the first experimental session Control/Placebo: completing the experimental session under normal sleep conditions Blinding: researchers evaluating subjects’ performance must not know which treatment is being applied at the time

You cannot assume that the numbers of complaints reflect the quality of the airlines. The airlines shown with the greatest number of complaints are the ones with the most passengers. You must consider the appropriateness of methods for presenting data; in this case displaying totals is misleading.

Answers will vary. Sample answer: The sample is not representative of the population of all college textbooks. Two reasons why it is not representative are that he only sampled seven subjects and he only investigated one textbook in each subject. There are several possible sources of bias in the study. The seven subjects that he investigated are all in mathematics and the sciences; there are many subjects in the humanities, social sciences, and other subject areas, (for example: literature, art, history, psychology, sociology, business) that he did not investigate at all. It may be that different subject areas exhibit different patterns of textbook availability, but his sample would not detect such results.

He also looked only at the most popular textbook in each of the subjects he investigated. The availability of the most popular textbooks may differ from the availability of other textbooks in one of two ways:

• the most popular textbooks may be more readily available online, because more new copies are printed, and more students nationwide are selling back their used copies OR
• the most popular textbooks may be harder to find available online, because more student demand exhausts the supply more quickly.

In reality, many college students do not use the most popular textbook in their subject, and this study gives no useful information about the situation for those less popular textbooks.

He could improve this study by:

• expanding the selection of subjects he investigates so that it is more representative of all subjects studied by college students, and
• expanding the selection of textbooks he investigates within each subject to include a mixed representation of both the most popular and less popular textbooks.

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Statistics and Probability Worksheets

Welcome to the statistics and probability page at Math-Drills.com where there is a 100% chance of learning something! This page includes Statistics worksheets including collecting and organizing data, measures of central tendency (mean, median, mode and range) and probability.

Students spend their lives collecting, organizing, and analyzing data, so why not teach them a few skills to help them on their way. Data management is probably best done on authentic tasks that will engage students in their own learning. They can collect their own data on topics that interest them. For example, have you ever wondered if everyone shares the same taste in music as you? Perhaps a survey, a couple of graphs and a few analysis sentences will give you an idea.

Statistics has applications in many different fields of study. Budding scientists, stock market brokers, marketing geniuses, and many other pursuits will involve managing data on a daily basis. Teaching students critical thinking skills related to analyzing data they are presented will enable them to make crucial and informed decisions throughout their lives.

Probability is a topic in math that crosses over to several other skills such as decimals, percents, multiplication, division, fractions, etc. Probability worksheets will help students to practice all of these skills with a chance of success!

Most Popular Statistics and Probability Worksheets this Week

Mean, Median, Mode and Range Worksheets

Calculating the mean, median, mode and range are staples of the upper elementary math curriculum. Here you will find worksheets for practicing the calculation of mean, median, mode and range. In case you're not familiar with these concepts, here is how to calculate each one. To calculate the mean, add all of the numbers in the set together and divide that sum by the number of numbers in the set. To calculate the median, first arrange the numbers in order, then locate the middle number. In sets where there are an even number of numbers, calculate the mean of the two middle numbers. To calculate the mode, look for numbers that repeat. If there is only one of each number, the set has no mode. If there are doubles of two different numbers and there are more numbers in the set, the set has two modes. If there are triples of three different numbers and there are more numbers in the set, the set has three modes, and so on. The range is calculated by subtracting the least number from the greatest number.

Note that all of the measures of central tendency are included on each page, but you don't need to assign them all if you aren't working on them all. If you're only working on mean, only assign students to calculate the mean.

In order to determine the median, it is necessary to have your numbers sorted. It is also helpful in determining the mode and range. To expedite the process, these first worksheets include the lists of numbers already sorted.

• Calculating Mean, Median, Mode and Range from Sorted Lists Sets of 5 Numbers from 1 to 10 Sets of 5 Numbers from 10 to 99 Sets of 5 Numbers from 100 to 999 Sets of 10 Numbers from 1 to 10 Sets of 10 Numbers from 10 to 99 Sets of 10 Numbers from 100 to 999 Sets of 20 Numbers from 10 to 99 Sets of 15 Numbers from 100 to 999

Normally, data does not come in a sorted list, so these worksheets are a little more realistic. To find some of the statistics, it will be easier for students to put the numbers in order first.

• Calculating Mean, Median, Mode and Range from Unsorted Lists Sets of 5 Numbers from 1 to 10 Sets of 5 Numbers from 10 to 99 Sets of 5 Numbers from 100 to 999 Sets of 10 Numbers from 1 to 10 Sets of 10 Numbers from 10 to 99 Sets of 10 Numbers from 100 to 999 Sets of 20 Numbers from 10 to 99 Sets of 15 Numbers from 100 to 999

Collecting and Organizing Data

Teaching students how to collect and organize data enables them to develop skills that will enable them to study topics in statistics with more confidence and deeper understanding.

• Constructing Line Plots from Small Data Sets Construct Line Plots with Smaller Numbers and Lines with Ticks Provided (Small Data Set) Construct Line Plots with Smaller Numbers and Lines Only Provided (Small Data Set) Construct Line Plots with Smaller Numbers (Small Data Set) Construct Line Plots with Larger Numbers and Lines with Ticks Provided (Small Data Set) Construct Line Plots with Larger Numbers and Lines Only Provided (Small Data Set) Construct Line Plots with Larger Numbers (Small Data Set)
• Constructing Line Plots from Larger Data Sets Construct Line Plots with Smaller Numbers and Lines with Ticks Provided Construct Line Plots with Smaller Numbers and Lines Only Provided Construct Line Plots with Smaller Numbers Construct Line Plots with Larger Numbers and Lines with Ticks Provided Construct Line Plots with Larger Numbers and Lines Only Provided Construct Line Plots with Larger Numbers

Interpreting and Analyzing Data

Answering questions about graphs and other data helps students build critical thinking skills. Standard questions include determining the minimum, maximum, range, count, median, mode, and mean.

• Answering Questions About Stem-and-Leaf Plots Stem-and-Leaf Plots with about 25 data points Stem-and-Leaf Plots with about 50 data points Stem-and-Leaf Plots with about 100 data points
• Answering Questions About Line Plots Line Plots with Smaller Data Sets and Smaller Numbers Line Plots with Smaller Data Sets and Larger Numbers Line Plots with Larger Data Sets and Smaller Numbers Line Plots with Larger Data Sets and Larger Numbers
• Answering Questions About Broken-Line Graphs Answer Questions About Broken-Line Graphs
• Answering Questions About Circle Graphs Circle Graph Questions (Color Version) Circle Graph Questions (Black and White Version) Circle Graphs No Questions (Color Version) Circle Graphs No Questions (Black and White Version)
• Answering Questions About Pictographs Answer Questions About Pictographs

Probability Worksheets

• Calculating Probabilities with Dice Sum of Two Dice Probabilities Sum of Two Dice Probabilities (with table)

Spinners can be used for probability experiments or for theoretical probability. Students should intuitively know that a number that is more common on a spinner will come up more often. Spinning 100 or more times and tallying the results should get them close to the theoretical probability. The more sections there are, the more spins will be needed.

• Calculating Probabilities with Number Spinners Number Spinner Probability (4 Sections) Number Spinner Probability (5 Sections) Number Spinner Probability (6 Sections) Number Spinner Probability (7 Sections) Number Spinner Probability (8 Sections) Number Spinner Probability (9 Sections) Number Spinner Probability (10 Sections) Number Spinner Probability (11 Sections) Number Spinner Probability (12 Sections)

Non-numerical spinners can be used for experimental or theoretical probability. There are basic questions on every version with a couple extra questions on the A and B versions. Teachers and students can make up other questions to ask and conduct experiments or calculate the theoretical probability. Print copies for everyone or display on an interactive white board.

• Probability with Single-Event Spinners Animal Spinner Probability ( 4 Sections) Animal Spinner Probability ( 5 Sections) Animal Spinner Probability ( 10 Sections) Letter Spinner Probability ( 4 Sections) Letter Spinner Probability ( 5 Sections) Letter Spinner Probability ( 10 Sections) Color Spinner Probability ( 4 Sections) Color Spinner Probability ( 5 Sections) Color Spinner Probability ( 10 Sections)
• Probability with Multi-Event Spinners Animal/Letter Combined Spinner Probability ( 4 Sections) Animal/Letter Combined Spinner Probability ( 5 Sections) Animal/Letter Combined Spinner Probability ( 10 Sections) Animal/Letter/Color Combined Spinner Probability ( 4 Sections) Animal/Letter/Color Combined Spinner Probability ( 5 Sections) Animal/Letter/Color Combined Spinner Probability ( 10 Sections)

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• Ace Your Statistics Homework with Hypothesis Testing

How to Tackle Hypothesis Testing in Your Statistics Homework

Hypothesis testing is a fundamental aspect of statistical analysis, often encountered in statistics homework . Understanding how to formulate hypotheses, conduct tests, and interpret results is crucial for success. This guide will help you navigate through the process of hypothesis testing, providing you with the necessary steps and tips to tackle similar assignments effectively. The first step involves clearly stating the null hypothesis (H0) and the alternative hypothesis (H1), which form the basis of your test. Next, check that your data meet the assumptions required for the statistical test you plan to use, such as normality and equal variances. After ensuring the assumptions are met, choose the appropriate test based on the type of data and the research question, such as a t-test for comparing means between two groups. Conduct the test using statistical software like jamovi, SPSS, or R, and obtain the test statistic and p-value. Make a decision about the null hypothesis based on the p-value and your predetermined alpha level, typically 0.05. Finally, write up your results in APA format, including the test statistic, degrees of freedom, p-value, and a brief interpretation of the findings. By following these steps, you can systematically and confidently approach hypothesis testing homework and ensure your analysis is both accurate and comprehensive.

Understanding Hypothesis Testing

Hypothesis testing is a critical statistical method used to make inferences about a population based on sample data. It involves formulating two competing hypotheses: the null hypothesis (H0), which suggests no effect or difference, and the alternative hypothesis (H1), which indicates the presence of an effect or difference. By conducting a statistical test and analyzing the resulting p-value, researchers can determine whether to reject the null hypothesis. This process helps to ascertain the likelihood that the observed data could have occurred under the null hypothesis, providing a foundation for making informed decisions and drawing conclusions in scientific research.

What is Hypothesis Testing?

Hypothesis testing is a method used to make decisions about a population based on sample data. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), then using statistical tests to determine which hypothesis is supported by the data.

Key Components of Hypothesis Testing

• Null Hypothesis (H0): A statement suggesting no effect or no difference. It is the hypothesis that researchers typically aim to test against.
• Alternative Hypothesis (H1): A statement that contradicts the null hypothesis, indicating the presence of an effect or a difference.
• Alpha Level (α): The significance level, usually set at 0.05, representing the probability of rejecting the null hypothesis when it is actually true.
• P-Value: The probability of obtaining the observed results, or more extreme, if the null hypothesis is true. A p-value less than α indicates that the null hypothesis should be rejected.

Steps to Tackle Hypothesis Testing in Your Statistics Homework

Step 1: formulating hypotheses.

Begin by clearly stating your null and alternative hypotheses. For example, if you are investigating whether room lighting affects memory recall, your hypotheses might be:

• H0: There is no difference in memory recall between the bright lighting group and the dim lighting group.
• H1: There is a difference in memory recall between the bright lighting group and the dim lighting group.

Step 2: Checking Assumptions

Before conducting the test, ensure that the data meet the assumptions of the chosen statistical test. Common assumptions include normality, independence, and homogeneity of variance. For example, if you are using a t-test, check that the data are approximately normally distributed and that the variances are equal across groups.

Step 3: Choosing the Appropriate Test

Select the statistical test based on your hypotheses and data characteristics. For comparing means between two independent groups, an independent-samples t-test is appropriate. For paired data, use a paired-samples t-test. For comparing proportions or categorical data, a chi-square test might be suitable.

Step 4: Conducting the Test

Using statistical software such as jamovi, SPSS, or R, perform the chosen test. Enter your data, run the analysis, and obtain the test statistics and p-value. For example, if you are analyzing memory recall data, input the scores for each group and run an independent-samples t-test.

Step 5: Making a Decision

Compare the p-value to your alpha level (typically 0.05). If the p-value is less than α, reject the null hypothesis. Otherwise, do not reject the null hypothesis. For instance, if your p-value is 0.03, you would reject the null hypothesis, suggesting that room lighting does have an effect on memory recall.

Step 6: Writing Up Results in APA Format

Present your findings clearly and concisely, following APA format. Include the test statistic, degrees of freedom, p-value, and a brief interpretation of the results. For example:

"An independent-samples t-test was conducted to compare memory recall in bright and dim lighting conditions. There was a significant difference in scores between the bright lighting group (M = 8.2, SD = 1.5) and the dim lighting group (M = 6.8, SD = 1.7); t(58) = 2.14, p = .03. These results suggest that room lighting significantly affects memory recall."

Example Application: Room Lighting and Memory Recall

Let's walk through an example similar to a typical homework question.

Formulating Hypotheses

• H0: There is no difference in memory recall between participants in bright and dim lighting conditions.
• H1: There is a difference in memory recall between participants in bright and dim lighting conditions.

Checking Assumptions

Using jamovi, check the data for normality and equal variances. If the data meet these assumptions, proceed with the t-test.

Conducting the Test

Input the recall scores into jamovi and perform an independent-samples t-test. Obtain the test statistic (t), degrees of freedom (df), and p-value.

Making a Decision

Compare the p-value to α = 0.05. If the p-value is below 0.05, reject the null hypothesis. If it is above, do not reject the null hypothesis.

Writing Up Results

"An independent-samples t-test was conducted to compare memory recall in bright and dim lighting conditions. The results indicated a significant difference between the bright lighting group (M = 15.3, SD = 4.2) and the dim lighting group (M = 12.1, SD = 3.8); t(58) = 2.73, p = .008. This suggests that lighting conditions significantly influence memory recall."

Tips for Success

• Understand the Theory: Ensure you have a solid grasp of statistical concepts and hypothesis testing theory.
• Use Software Efficiently: Familiarize yourself with statistical software like jamovi, SPSS, or R to streamline the analysis process.
• Check Assumptions: Always verify that your data meet the necessary assumptions for the test you are conducting.
• Practice APA Formatting: Learn the APA format for writing up results to ensure your assignments are professionally presented.

Hypothesis testing is an essential skill in statistics, helping to make informed decisions based on data. By following the steps outlined in this guide—formulating hypotheses, checking assumptions, choosing the appropriate test, conducting the test, making decisions, and writing up results—you can tackle hypothesis testing in your statistics homework with confidence. Practice these steps regularly, and you'll find that hypothesis testing becomes a manageable and even enjoyable part of your statistical analysis. Happy studying!

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