If we have a large voluntary response sample consisting of weights of subjects who chose to respond to a survey posted on the Internet, can a graph help to overcome the deficiency of having a voluntary response sample?Choose the correct answer below.O A. Yes, a graph can help to overcome the deficiency. Any graph that is given with a sufficiently accurate description of any deficiencies in the sampling technique is no longer considered biased.O B. No, a graph cannot help to overcome the deficiency. Before graphing, all inaccurate values and outliers must be removed from the data set.OC. No, a graph cannot help to overcome the deficiency. If the sample is a bad sample, there are no graphs or other techniques that can be used to salvage the data.O D. Yes, a graph can help to overcome the deficiency. Certain graphs that hide any specific values in the data, such as pie charts, can be used to hide deficiencies in the sampling technique.

Given : If we have a large voluntary response sample consisting of weights of subjects who chose to…

Answered: If we have a large voluntary response…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The book The Wall Street Journal. Guide to Information Graphics by Dona M. Wong gives strategies for using graphs and charts to display information effectively. One popular graph discussed is the donut pie chart. The donut pie chart is simply a pie chart with the center removed. A recent Harris Poll asked adults about their opinions regarding whether books should be banned from libraries because of social, language, violent, sexual, or religious content. The responses by education level to the question "Do you think that there are any books which should be banned completely?" are shown in the following donut pie charts. (a) What feature of Keith's graph makes it difficult to visually compare the responses of those with some college to those shown in the other graphs? (Select all that apply.) a)The graphs made by Keith and Ramon compare groups across education level. b)The graphs made by Keith and Ramon are all donut pie charts. c)The graphs do not have data labels showing the…
This problem demonstrates a possible (though rare) situation that can occur with group comparisons. The groups are sections and the dependent variable is an exam score. Section 1 Section 2 Section 3 74.5 69.7 85.4 85.1 72.5 82.9 80.3 45.7 78.8 88.8 84.4 79.4 66.4 62.4 68 72.5 48.3 78 83.1 88 69.7 79.4 61.5 76.2 71.4 67.3 74.9 Run a one-factor ANOVA (fixed effect) with α=0.05α=0.05. Report the F-ratio to 3 decimal places and the P-value to 4 decimal places.F=F= Correctp=p= CorrectWhat is the conclusion from the ANOVA? reject the null hypothesis: at least one of the group means is different fail to reject the null hypothesis: not enough evidence to suggest the group means are different Correct Calculate the group means for each section:Section 1: M1=M1= CorrectSection 2: M2=M2= CorrectSection 3: M3=M3= CorrectReport means accurate to 2 decimal places.Conduct 3 independent sample t-tests for each possible pair of sections. (Though we will see later…
Draw the appropriate graph for each of the data sets given below. Explain the chosen graphs and give a short interpretation
Part E. Please carefully examine this graph: 5'7" 5'6" 5'5" 5'4" 5'3" 5'2" 5'1" 5'0" Average Female Height per country Latvia Australia Scotland Peru South Africa India 12. Is this a univariate or a bivariate graph? 13. This is a stylized version of what kind of graph (bar, pie, line, boxplot, histogram, stem- and-leaf, frequency polygon, ogive)? 14. What are the two key ways in which this graph is misrepresenting the data?
This problem demonstrates a possible (though rare) situation that can occur with group comparisons. The groups are sections and the dependent variable is an exam score. Section 1 Section 2 Section 3 56 38.1 59.5 51.1 22.3 44.6 43 61 62 61.7 24.9 52.8 59.7 49.1 51.5 49.1 64.6 55.4 56.9 39 54.6 65.4 46.3 48.3 48 45.3 56 Run a one-way ANOVA (fixed effect) with a = 0.05. Round the F-ratio to three decimal places and the p- value to four decimal places. Assume all population and ANOVA requirements are met. F = p = What is the conclusion from the ANOVA? O reject the null hypothesis: at least one of the group means is different O fail to reject the null hypothesis: not enough evidence to suggest the group means are different
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This problem demonstrates a possible (though rare) situation that can occur with group comparisons. The groups are sections and the dependent variable is an exam score. Section 1 Section 2 Section 3 F= 60.5 62.5 76.8 68.3 59.4 71.1 73.1 67.4 54.4 p= 49.5 76 57.7 56.7 33.7 60.5 50.4 72.4 36.3 59.7 70.9 56 73.4 66.8 64.2 Run a one-way ANOVA (fixed effect) with a = 0.05. Round the F-ratio to three decimal places and the p- value to four decimal places. Assume all population and ANOVA requirements are met. 66 67.4 62.9 What is the conclusion from the ANOVA? O reject the null hypothesis: at least one of the group means is different fail to reject the null hypothesis: not enough evidence to suggest the group means are different
A graphing calculator is recommended.The following table lists the number of pages in four different types of magazines. Home decorating News Health Computer 175 89 85 104 287 95 157 139 165 123 91 98 209 107 106 209 199 101 97 147 Using a significance level of 5%, test the hypothesis that the four magazine types have the same average length. (Let 1 = Home decorating, 2 = News, 3 = Health and 4 = Computer.) 1.)Enter an exact number as an integer, fraction, or decimal.df(num) = 2.) Enter an exact number as an integer, fraction, or decimal.df(denom) = 3.)What is the test statistic? (Round your answer to two decimal places.) 4.)What is the p-value? (Round your answer to four decimal places.) 5.)(i) Alpha (Enter an exact number as an integer, fraction, or decimal.)? =
The association between occurrence of convictions and family income was examined by following a cohort of 395 boys for about 20 years, starting at age 8-9. The following table shows number of convictions with respect to three family income brackets: a)What type of table is this? b) Display the same data using a mosaic plot. c) What type of variable is income level? How should this affect your graph? d) By viewing the table and the graph, describe any apparent association between income and later convictions. e) Does the table or the graph better reveal the association between convictions and income? Pls help and explain all parts correctly, thank you

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