A particular article reported the accompanying data on phenotypes resulting from crossing tall cut-leaf tomatoes with dwarf potato-leaftomatoes. There are four possible phenotypes: (1) tall cut-leaf, (2) tall potato-leaf, (3) dwarf cut-leaf, and (4) dwarf potato-leaf. Mendel'slaws of inheritance imply that π₁ = 9/16, π₂ = 3/16, л3 = 3/16, and л4 = 1/16. Are the data from this experiment consistent with Mendel'slaws? Use a 0.01 significance level. (Use 2 decimal places.)Phenotype1 2 3 4Frequency 925 289 294 103x²= 1.178×

Step 1: Calculate the total observed frequency.In this case, we have to add the frequency values…

Answered: A particular article reported the…

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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On each trial of an experiment, a subject is presented with a constant soft noise, which is interrupted at some unpredictable time by a noticeably louder sound. The time it takes for the subject to react to this louder sound is recorded. The following list contains the reaction times (in milliseconds) for the 16 trials of this experiment: 285, 175, 164, 217, 273, 222, 212, 202, 236, 229, 171, 235, 193, 186, 261, 241 Send data to calculator th Find 40" and 75" percentiles for these reaction times. (a) The 40 th percentile: || milliseconds (Ь) The 75 th percentile: milliseconds
Having trouble understanding this chapter. Was hoping to get a solution to these questions to help me understand the concept better.
A QR code photographed in poor lighting, so that it can be difficult to distinguish black and white pixels. The gray color (X) in each pixel is therefore coded on a scale from 0 (white) to 100 (black). The true pixel value (without shadow) the code is Y = 0 for white, and Y = 1 for black. We treat X and Y as random variables. For the highlighted pixel in the figure is the gray color X = 20 and the true pixel value is white, i.e. Y = 0. We assume that QR codes are designed so that, on average, there are as many white as black pixels, which means that pY (0) = pY (1) = 1/2. In this situation, X is continuously distributed (0 ≤ X ≤ 100) and Y is discretely distributed, but we can still think about the simultaneous distribution of X and Y. We start by defining the conditional density of X, given the value of Y : fX|Y(x|0) = "Pixel is really white" fX|Y(x|1) =" Pixel is really balck " Use Bayes formula as given in the picture and find the probability for x = 20 like in the picture.
An article reports on an experiment in which each of five groups consisting of six rats was put on a diet with a different carbohydrate. At the conclusion of the experiment, the DNA content of the liver of each rat was determined (mg/g liver), with the following results: Carbohydrate Xi. Starch 2.58 Sucrose 2.63 Fructose 2.13 Glucose 2.41 Maltose 2.49 Assume that EEx;;2 = 183.9. Construct at CI for ij e = µ1 - (H2 + µ3 + H4 + H5)/4 which measures the difference between the average DNA content for the starch diet and the combined average for the four other diets. (Use a 95% confidence interval. Round your answers to three decimal places.) mg/g liver
A sample of n= 25 scores has mean of m=68. Find the Z score for this this sample: A) If it was obtained from a population with mu= 60 and sigma=10 Z=___ B) if it was obtained from a population with mu= 60 and sigma =20 Z=__ C) if it was obtained from a population with mu= 60 and sigma = 40 Z= __
A study of fox rabies in southern Germany gave the following information about different regions and the occurrence of rabies in each region. A random sample of n1 = 16 locations in region 1 gave the following information about the number of cases of fox rabies near that location. x1: Region I Data 3 7 8 7 5 8 8 1 3 3 3 2 5 1 4 6 A second random sample of n2 = 15 locations in region II gave the following information about the number of cases of fox rabies near that location. x2: Region II Data 4 2 4 1 3 8 5 4 4 4 2 2 5 6 9 Note: If a two-sample t-test is appropriate, for degrees of freedom d.f. not in the Student's t table, use the closest d.f. that is smaller. In some situations, this choice of d.f. may increase the P-value by a small amount and therefore produce a slightly more "conservative" answer.Use a calculator with sample mean and sample standard deviation keys to find x1 and s1 in region I, and x2 and s2 in region II. (Round your answers to two…
Q.6.2 The financlal manager of a natlonal warehouse chaln has found from prevlous experlence that 45% of clients pay by credit card, 35% pay on account, whille the remainder pay using cash. He wishes to know if this is still the case. A random sample of 1000 sales receipts from the last month produced the following results: Payment Method Credit Card Account Cash Total Number of receipts 500 315 185 1000 Using a 1% significance level, test whether the payment method pattern has changed.
The U.S. Energy Information Administration claimed that U.S. residential customers used an average of 10,95110,951 kilowatt hours (kWh) of electricity this year. A local power company believes that residents in their area use more electricity on average than EIA's reported average. To test their claim, the company chooses a random sample of 184184 of their customers and calculates that these customers used an average of 11,162kWh11,162⁢kWh of electricity last year. Assuming that the population standard deviation is 1263kWh1263⁢kWh, is there sufficient evidence to support the power company's claim at the 0.050.05 level of significance? Step 2 of 3 : Compute the value of the test statistic. Round your answer to two decimal places.
A major oil company has developed a new gasoline additive that is supposed to increase mileage. To test this hypothesis, ten cars are randomly selected. The cars are driven both with and without the additive. The results are displayed in the following table. Can it be concluded, from the data, that the gasoline additive does significantly increase mileage? Let d=(gas mileage with additive)−(gas mileage without additive)�=(gas mileage with additive)−(gas mileage without additive). Use a significance level of α=0.05�=0.05 for the test. Assume that the gas mileages are normally distributed for the population of all cars both with and without the additive. Car 1 2 3 4 5 6 7 8 9 10 Without additive 27.2 13.7 12.5 13.4 14.7 25.5 10.3 13.9 14.5 25 With additive 29.7 15.7 14.1 16.4 17.8 27.8 12.1 15 17.3 28 Copy Data Step 1 of 5: State the null and alternative hypotheses for the test.
In Mendel's experiment, he obtained 724 plants with red flowers and 210 with white flowers in his cross of red flowered x white flowered pea plants. Is this result consistent with his hypothesis of factor segregation? Calculate the x and obtain the approximate value of P from Table 1, then interpret the results and clearly state your conclusion. Table 1: Chi-square table Chi Square Values and Probability Degrees of Freedom P= 0.99 0.95 0.80 0.50 0.20 0.05 0.01 1 0.000157 0.00393 0.0642 0.455 1.642 3.841 6.635 2 0.020 0.103 0.446 1.386 3.219 5.991 9.210 3. 0.115 0.352 1.005 2.366 4.642 7.815 11.345 0.297 0.711 1.649 3.357 5.989 9.488 13.277
Suppose we are developing a new drug that is supposed to improve the recovery time of an illness. We want to investigate if this is true. We conduct an experiment: we randomize twenty participants into two groups of size n = 10 each. In one group, we give the participants the drug. In the other group, we give them a placebo. We measure the recovery time of the participants in days. We observe the following data: • In the group given the drug, we observe recovery times (yı,..., Y10) = (15, 10, 13, 7,9, 8, 21,9, 14, 8), with ĝ1 = 11.4. • In the group given the placebo, we observe recovery times (yı1,..., Y20) = (15, 14, 12, 8, 14, 7, 16, 10, 15, 12) with j2 = 12.3. Assume that the data in each group follow Normal(µ1,0²) and Normal(42, o²) distributions respec- tively for the drug and placebo groups, o2 15. We want to test the following hypothesis: Ho : µ1 – 12 = 0 versus HA: µ1 – 42 < 0, using the test statistic T(Y) = Y1 – Ý2. a) Define the rejection region as {y : ĝı – 2 < c1} where ci…
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