Find the sum of squares, degrees of freedom, mean squares, F, PvalueSource: Planting Density, Error, Total Problem Solving12. An agronomy researcher was interested in determining the relationshipbetween the number of wheat plants per unit area and grain production at afixed fertility regimen. The experiment consisted of single factor (PlantingDensity at four levels: 20, 30, 40 and 50 plants per quarter-square meter plot) ina completely randomized design with three (3) replicate plots per plantingdensity. The response for this experiment is yield in grams per plot. The data forthis experiment appear in the following table:Planting Density2030405016.018.617.618.0Grain15.520.219.316.4Yield (gm)16.518.217.116.6

This is a two-way Analysis Of Variance problem, with two factors, namely, planting density and grain…

Answered: 12. An agronomy researcher was…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.6: Summarizing Categorical Data

Problem 10CYU

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Find the sum of squares, degrees of freedom, mean squares, F, Pvalue Source: Planting Density, Error, Total

Problem Solving
12. An agronomy researcher was interested in determining the relationship
between the number of wheat plants per unit area and grain production at a
fixed fertility regimen. The experiment consisted of single factor (Planting
Density at four levels: 20, 30, 40 and 50 plants per quarter-square meter plot) in
a completely randomized design with three (3) replicate plots per planting
density. The response for this experiment is yield in grams per plot. The data for
this experiment appear in the following table:
Planting Density
20
30
40
50
16.0
18.6
17.6
18.0
Grain
15.5
20.2
19.3
16.4
Yield (gm)
16.5
18.2
17.1
16.6

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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