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STATS 250 Lecture Notes - Lecture 7: Snoring, Binomial Test, Null Hypothesis

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10 Oct 2016

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Brenda Gunderson

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STATS 250 Full Course Notes

STATS 250 Full Course Notes

Document Summary

P-value measures how compatible is your data with ho. )f it"s not compatible under (o, then it is more likely to favor (a. If the p-value is small, you reject the null and go with the new theory. If the p-value is small, you reject the null hypothesis. You say your results are statistically significant at that level of significance that you picked up front. When p-value is not small, we fail to reject ho and say the results are not statistically significant. The picture of the p-value will be some probability that is under the model for your test statistic. If the results are so unusual that they will happen less than 10% of the time and ho the left. Same thing with right but shade to the right side. For the z model, it"s a normal curve. )f the direction is to the left, we"re going to shade wherever we"re at and shade to.

Related textbook solutions

Introductory Statistics

OER Edition, 2013

ISBN: 9781938168208

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Related Questions

(14 marks) Fortune magazine publishes a list of the world’s billionaires each year. We will examine the top 97 of the 1992 list. Their wealth, age, and geographic location (Asia, Europe, Middle East, United States, and Other) are reported. Wealth is a right-skewed variable, so we will consider the natural logarithm log wealth to be the response and will see if age and geographic location are predictors.

(a) (2 marks) Let

Ebe a variable that is 1 if the person is from Europe and 0 otherwise,

Mbe a variable that is 1 if the person is from the Middle East and 0 otherwise,

Obe a variable that is 1 if the person is from the “Other” region and 0 otherwise,

Ube a variable that is 1 if the person is from the United States and 0 otherwise.

State a linear model for the mean of log wealth that includes age and the above 4

geographic variables. Call this the full model.

(b) (5 marks) The SSY for these data is 28.3351 and the SSE from ﬁtting the full model

is 27.0461. Use this information to construct an ANOVA table. Your table should

include columns for Source, df, SS, MS and F, and should include rows for the model

(full model), residual and total.

(c) (2 marks) In addition to the full model, the reduced model that includes only an

intercept and age is ﬁt. What is the null hypothesis being considered by ﬁtting these

two models? (Refer to quantities deﬁned in your model.)

(d) (3 marks) The SSM from the reduced model is 59.7. Calculate an F-statistic to test the hypothesis of part (c). State the degrees of freedom for the F-distribution

you would compare this statistic to. (You do not need to calculate the p-value or actually test the hypothesis.)

(e) (1 mark) Using terminology from class, name the kind of Ftest that the statistic in part (d) corresponds to.

(f) (1 mark) If the null model for these data is compared to the model that includes an

intercept and age, what are the results?

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