Define each of the following and provide a specific example for each type of statistical test or concept. - The null and alternative hypotheses - Type I and Type II errors - The proper use of statistical software - Cross-tabulation - Chi-Square - Single sample t-test - Independent t-test - One-Way ANOVA Show y
Question 1: Hypothesis testing allows you to verify whether a supposition is correct. By considering the variables, you may also be able to analyze the reason why the hypothesis is proven correct or incorrect. Describe in your own words the differences between type I and type II errors. In addition to your explanation, you ma
Why is it important to know the standard deviation for a given sample? What do researchers learn about a normal distribution from knowledge of the standard deviation? A sample of n=20 has a mean of M = 40. If the standard deviation is s=5, would a score of X= 55 be considered an extreme value? Why or why not? Can you please d
Could you please explain Stratification to me in layman's terms and then read the attached article and detail how it was used therein? Reference: Lipchik, G. L., Nicholson, R. A., & Penzien, D. B. (2005). Allocation of patients to conditions in headache clinical trials: randomization, stratification, and treatment matching.
Find a research article; find the obtained value, and its level of significance. Discuss how comfortable you are with the inferences made by the researcher based on the theories of Type I and Type II errors.
Please help with the following problems. 1. Whether the appropriate analysis would be a one or two tailed test 2. A type I and type II error given the context of the hypothesis. The Hypothesis A. Cognitive behavior therapy (CBT) will be better than supportive therapy in reducing children's anxiety at posttreatment.
Define a type I error and explain why it occurs. Explain a factor that the researcher can control to change the type I error. Also, explain how type I errors can be avoided. Define a type II error and explain why it occurs. How do sample size, selection of alpha level, and precision of measurement affect the type II error rat
In the last few years, an organization has conducted 200 clinical trials to test the effectiveness of anti-anxiety drugs. Suppose, however, that all of those drugs were obtained from the same fraudulent supplier, which was later revealed to have been sending only inert substances (e.g., distilled water, sugar pills) instead of r
I need a real-world situation where Type I and Type II errors can occur and state the null and alternative hypotheses for that example. Could you please also explain what the Type I and Type II errors are for that example?
Please explain the difference between a Type I and a Type II error when testing a hypothesis. Please provide an example of each.
1. The SEM for a particular intelligence test (mean of 100, standard deviation of 15) is 3 points. Ken Garoo obtains an IQ score of 126, but needs an IQ of 130 to qualify for a Talented and Gifted (TAG) class. Calculate the range of Ken's true score: (a) with 68% probability, and (b) with 95% probability. Should Ken be admitted
Please help with the following problem. In the US legal system, a defendant is presumed innocent until proven guilty. Consider a null hypothesis, Ho: that the defendant is innocent, and an alternative hypothesis, Ha: that the defendant is guilty. Explain the meaning of a jury committing a Type I error and of committing a Ty
1. You have been asked to evaluate if a particular coin is fair or not. You have decided to use the following test: Accept that the coin is fair if in 30 tosses the coin gives between 11 and 19 heads (inclusive); reject the hypothesis of fairness otherwise. Compute the Type I error rate of this test. Interpret, in plain wor
Type I error is used in selecting the appropriate alpha level. Based on your understanding, why is Type I error more important than Type II error in selecting the appropriate alpha level?
Given the following hypothesis test, what are the ramifications of a type I and type II error? Just reply in a sentence or two for each case. Forty perccent of overweight people have at least one symptom of disease X. A new diet plan purports to reduce the incidence of disease X symptoms in the overweight population. Using a
Is it more important for the researcher to be concerned with Type I or Type II errors in a study? Why do these error types only apply to the analysis of data sets, rather than individual instances?
Given the following information, would your decision be to reject or fail to reject the null hypothesis? Setting the level of significance at .05 for decision making, please provide an explanation for your conclusion to help me understand the concepts. a) The null hypothesis that there is no relationship
Metal detectors at airports are used to determine whether passengers are carrying weapons. If the null hypothesis states that a passenger isn't carrying a weapon, a type I error would occur whenever A) a weapon-free passenger passes the detector without activating the alarm. B) a weapon-free passenger passes the detector and
8.4. What are the five steps to create a confidence interval for a z distribution? 8.6. What effect does increasing the sample size have on the standard error and the test statistic for every hypothesis test? 8.8. What does it mean to say the effect-size statistic, such as Cohen's d, neutralizes the influence of sample siz
1. The SEM for a particular intelligence test (mean of 100, standard deviation of 15) is 3 points. Ken Garoo obtains an IQ Score of 126, but needs and IQ of 130 to qualify for a Talented and Gifted (TAG) class. Calculate the range of Ken's true score: (a) with 68% probability, and (b) with 95% probability. Should Ken be admi
A soft-drink machine at a steak house is regulated so that the amount of drink dispensed is approximately normally distributed with a population mean of 200 millilitres and a standard deviation of 15 millilitres. The new machine is checked periodically by taking a sample of 9 drinks and computing the average content. If x̅ fall
Explain whether the following statements are correct. A type II error is the error of rejecting the null hypotheis when it is true. The type II error is denoted by (1-beta). Therefore the statistical power is the compliment of the risk of type II error. Factors that increase statistical power also decrease the risk of a t
Can anyone tell me what type of test were used to come up with the solution attached to this email? the question was ask below: What test did you use to complete the problem 14-65 and 14-68? I see were others using Mann-Whitney and other test.
A researcher collects data on children's weights from a random sample of children in the South and concludes that children in the South weigh less than the national average. The researcher, however, does not realize that the sample includes many children who are small for their age and that in reality, there is no difference in
1. Suppose you time how long it takes every student to complete this test, and assume that the results have a normal distribution with a mean of 120 minutes, and a standard deviation of 30 minutes. Let X be the time it will take you to complete the test. a. What is the probability that X is between 100 and the mean? b. Find P
In terms of correctness of a study, I agree type one errors can be very important. With Type II errors there are more negative consequences if the result is wrong but assumed to be correct. Do you think that there would be significant consequences if the study were to be correct but assumed to be negative?
#1. An investigator wants to estimate caffeine consumption in high school students. How many students would be required to ensure that a 95% confidence interval estimate for the mean caffine intake(measured in mg) is within 15 units of the true mean? Assume that the standard deviation in caffine intake is 68 mg. #2. Consid
Question 1: What is a type I and type II errors in hypothesis testing? What would be examples of each? Explain Question 2: What is the difference between statistical significance and practical significance? Why is statistical significance not necessarily of practical important difference to a business decision? Provide a
Identifying Type I and II error that corresponds to the given hypothesis. The percentage of households with at least two cell phones is less than 60%. (i) Type I error (in the words of the problem): (ii) Type II error (in the words of the problem):
1. Find the critical z values. In each case, assume that the normal distribution applies Left-tailed test, α =0.05 2. Α = 0.005; H1 is p ≠ 0.20 3. Use the given information to find the P-value The test statistic in a two-tailed test is z= -1.63 4. With H1:p<0.32, the test statistic is z=-1.90 5.