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Observation in Each Sample

创建日期：2024-03-29 11:45:12

所属分类：统计学statistics

标签： Stat230

Observation in Each Sample

Stat 230 Assignment 6 2020W2

Question 1

Suppose we have I samples (each of size J): X1, X2, · · · , XI , taken from each of I possibly

different populations. All observations are independent, inside and between the samples. The

table below shows information of each samples

Sample

Observation in

Each Sample

Question 2

(8 points)An experiment was conducted in which four brands of tires were compared for traction

on ice. Three measurements of stopping distance were taken for each type of tire.

In the experiment, a single car was used. In each experimental run, the distance over which

the car could decelerate from 20 km/h to 0 km/h on an artificial ice surface was measured.

Tire Brand Stopping Distance

Compute the treatment group averages and the residuals. Do the ANOVA and decide whether

the true mean stopping distances are different for the different brands at the .05 level.

Question 3

(5 points) The time in months before paint started to peel for five brands of paint applied to

a set of test panels is summarized below:

Paint No. of Panels ˉxi· s

A 6 48.6 30.5

B 6 51.2 30.2

C 6 60.1 31.8

D 6 55.2 33.1

On the basis of residual plots, the data can be modeled as normal, and the measurements

appear to be independent. Is there evidence at the 5% level of a difference in the mean time

to peel for the different panels?

Question 4

(4 points)The data set PlantGrowth is available in R. It contains weight measurements on

30 plants grown under 3 different experimental conditions (10 in each condition). Here is the

output from the aov command in R:

Df Sum Sq Mean Sq F value Pr(>F)

group 2 3.7663 1.8832 4.8461 0.01591 *

Residuals 27 10.4921 0.3886

Is there evidence that at least one experimental condition yields plants of a different mean

weight?

Question 5

An individual’s critical flicker frequency (cff) is the highest frequency (in cps) at which the

flicker in a flickering light source can still be detected. At frequencies above the cff, the light

source appears to be continuous even though it is actually flickering. A preliminary investigation

was conducted to see if true average cff depends on iris color. The results are given below from

an ANOVA carried out in R. An equal number of rats were fed one of three diets (Beef, Pork,

or Cereal) in order to investigate weight gain. The partial results from an ANOVA carried out

in R follow below.(Data sourced from the graonva package in R)

Df Sum Sq Mean Sq F value

Diet 267

Residuals 57 15932

(a) (1 point) How many rats were used in this study?

(b) (4 points) Complete this ANOVA table and interpret the result of the associated F-test.

Question 6

(8 points) Suppose x1, x2, . . . , xn come from a Poisson distribution p(x) = e?λλ

, where x =

0, 1, 2, . . . with unknown parameter λ. Find the maximum likelihood estimator for λ.

Question 7

(5 points) Consider a population governed by the discrete distribution p(x), where p(x) = θ

for x = 1 and p(x) = 1 ? θ for x = 0, where θ ∈ [0, 1]. Three independent observations are

{0, 1, 0}. Find the likelihood function

Page 2

Question 8

Suppose 5 independent measurements 1, 3, 1, 7, 3 are taken from an exponentially distributed

population f(x) = λe?λx

, where x > 0

(a) (5 points) Find the maximum likelihood estimate for λ.

(b) (4 points) Find the maximum likelihood estimate for the probability that the next independent

measurement taken from the population is greater than 3.

Page 3

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239 QF5203 INFR08010 IT114105 FIT2093 ECON3124 ECON1195 MATH 337 STAT 3006 COMP202 COMP3130 MATH3609 COMP 250 CS6140 IEEE ELE00041I FIN40090 CIV 5899 MATH3066 IGNMENT MATH 2009 STAT3405 HIST 101 MATH 3281 CEGE0042 ICT532 LAB 7 LAB 5 MCO455 CSIT214 Q4 IFB104 A1 ECO220Y5Y DA5020 CMPSC473 FIN9007 DSCI553 MSCI534 COMP3308 CSE-112 CMPT 310 EE104 F 2C P20 ALY2010 BUSM060 STA258 ECO00030M R BIOSTAT 274 COS6012-B FIT3155 CMPUT 340 EC421 INFS4205 ECOM135 NATS 1740 COMP809 MBE 6005 STA465 CSSE2310 CIVL2700 DATA4700 CMPSC 473 ISE 529 CS5044 MAST30020 COMP2207 ENGG1001 COMP0046 FIT3165 STAT GR5241 MECH0007 vATHK1001 ANALYTIC ATHK1001 MATH352001 HW3 S1 BMAN 24662 COMP 636 Stat-461 STAT 302 STAT 2132 STAR534 ENG4137 CMP3752M CS3103 BISM3222 STA 135 ME155A IIMT3601 ECON3371 ECON 3371 HW4 FINA 5840 DT211C CTEC3902 MAT005 MATH2148 S261F Econ 332 MATH3734 MIS41270 7CCMFM13 SYST 664 CIS434 CENG10014 MT4111 MT4527 ECMM424 CMT219 Math 136 MATH 3120 COMP10002 MAST20009 MATH0058 BEEM117 ISYE 6420 MGMTMFE 405 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