In regression model we don't need normality assumption until we have to find confidence interval.
So whenever you have to construct confidence interval you have to examine normality.
When is it not necessary to examine the Normality (QQ Plot) assumption?
What is the assumption of normality? If a researcher is conducting the Mann-Whitney Test, does this mean that their data have met the assumption of normality or failed to meet the assumption of normality? Explain your answer.
Construct a normal probability plot for the residuals. Comment
on the normality assumption.
Use MINITAB package software/other software to compute
and plot your data (No manual calculation is required)
Value of $1000 Year 2014 1863 2013 1639 Year-X (Independent) Value of $1000 Y-Dependent 2012 1239 2011 1068 2010 1046 2009 909 719 2008 2007 1141 2006 1081 2005 934 2004 890 803 2003 624 2002 801 2001 2000 909
Value of $1000 Year 2014 1863 2013 1639 Year-X (Independent)...
Matching a Distribution to a QQ Plot 4 puntos posibles (calificables) Consider an iid sample X1, X2,..., X, id P that has been reordered as X(1) < X(2) S... 5X(n). In each image below, we have chosen a different distribution for P and compared the empirical quantiles to the standard Gaussian quantiles using a QQ plot. Assume that n is large enough so that the QQ plot starts to look like a continuous curve. For each plot, match the QQ...
If the Durbin-Watson statistic has a value close to 0, which assumption is violated? a) Normality of the errors. b) Independence of errors. c) Homoscedasticity. d) None of the above.
Question 19 1 pts In ANOVA, the assumption of normality is... the population is normally distributed the individual scores are normally distributed the residuals are normally distributed the group scores are normally distributed Question 20 1 pts In ANOVA, the assumption of independence is... the groups are independent, no overlapping group members the scores are independent, no correlation between scores from different groups the residuals are independent the residuals are correlated
Why is the normality assumption essential to the interpretation of the capability index? A)Because a spread of 6 standard deviations represents 99.73% of cases B) Because the normal distribution always has a mean of 0 C) Because only normal distributions are capable of statistical control D) Because the specifications are always explained by the bell curve
How would you interpret this QQ plot with the two
variables quantiles being compared (Bike$casual, and
Bike$registered)?
Q-Q Plot of BikeSregistered vs. BikeScasual 寸 0 100 200 300 Quantiles of Bike$casual
We studied a characteristic of iron. Under the normality
assumption of its distribution
and using its sample mean and standard deviation, we computed the
following confidence
interval [2271:7688; 2308:2312]. This interval is a confidence
interval for the mean
of that characteristic at a level of confidence of 90%. We are told
the sample size is 16
and the sample mean is x = 2290. What is the value of the sample
standard deviation s?
We studied a characteristic of iron....
20. Look at the following QQ plot which compares the distribution of two samples of wind speeds x and y 6 4 0 0 10 15 X Quantiles What does this show: A. B. C. D. The main mode of x comes before the main mode of y x has a heavier tail The distributions are identical The main mode of x comes after the main mode of y 5%
20. Look at the following QQ plot which compares the...
We studied a characteristic of iron. Under the normality assumption of its distribution and using its sample mean and standard deviation, we computed the following confidence interval [2271.7688,2308.2312]. This interval is a confidence interval for the mean of that characteristic at a level of confidence of 90%. We are told the the sample size is 16 and the sample mean is x= 2290. What is the value of the sample standard deviations?A. 44.33 B. 41.6 C. 83.2 D. 54.38 E....