I want to summarize what is the most and least resistant to salinity? Mean Shoot_lenghtAccessibility25.0020.0015.00-10.005.00-0.00-Figure 2.5: Effect of salinity concentration and cultivars.control3dS6dSTreatment9dS12dSCultivars1.002.003.004.005.0016.007.008.009.0010.0011.0012.0013.0014.0015.00 <12:30treatmentControl3ds6ds9d$12dSAccording to Figure 2.4 denoting the same outcome as in Figure 2.2. The numeric value of meanshoot length is displayed in the graph. The highest mean shoot length 3ds (11.22), followed bycontrol (7.24), 6ds (7.96), 9dS (4.45) and 12dS (2.64) has the lowest mean shoot length. That ismean the means shoot length are not same between five treatments. the mean shoot length for3ds treatment is higher than the other treatments. As salinity increases from 3ds, their meanshoot length decreases.Table 2.3: Showing Highest and Lowest Mean Shoot Length in Treatments.Height means shoot weightCultivar 5Cultivar 5Cultivar 5Cultivar 5Cultivar5Accessibility: InvestigateToday12:23 PM3EiEditLowest mean shoot weightCultivar 1Cultivar 14Cultivar 7Cultivar 14,12Cultivar 1,12,14Eb

Cultivars 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00…

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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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According to the CDC, cholesterol levels can be reduced by following a healthy diet, getting regular exercise, and reducing the amount of alcohol consumed on a weekly basis. One method of monitoring overall cholesterol levels is to calculate your cholesterol ratio (LDL/HDL), in general a cholesterol ratio between 3.5 and 5.0 is considered to be healthy for most adults. Suppose you are a clinical researcher testing the effects of these lifestyle changes on patient cholesterol levels. In order to determine if following these guidelines helps to reduce overall cholesterol, a total of 18 participants (N = 18) with moderate to high cholesterol ratios (i.e., 3.91 to > 5.0) were recruited for a healthy lifestyle study and their cholesterol ratio was calculated three times over a six week period: Week 0 (baseline), Week 3, and Week 6. Using the variables "Week 0", "Week 3", and "Week 6" in the data set, conduct a One-Way, Within Subjects (AKA Repeated Measures) ANOVA, at α = 0.05, to see…
There are three types of contaminants that spoils water. Organic pollutants (O), volatile solvents (V), and chlorinated compounds (C). A new analytical method to detect (D) contaminants in water is being tested. The makers of the test claim that it can detect high levels of organic pollutants with 98% accuracy, volatile solvents with 99% accuracy, and chlorinated components with 89% accuracy. If a pollutant is not present, the test does not signal. Samples are prepared for the calibration of the test and 65% of them are contaminated with organic pollutants, 20% with volatile solvents, and 15% with traces of chlorinated compounds. A test sample is selected randomly. (a) What is the probability that the test will signal? (b) If the test signals, what the probability that volatile solvents are present? (c) If the test does not signal, what is the probability that chlorinated compounds are present? Note: Use the notations in the brackets to describe the events.
I have collected real data on the sale of a microwavable cup of soup across 20 different cities for the same time period (a month). The variables in the dataset are: Quantity sold in the city for that month: Measured in thousands of units Price: measured in dollars Average Income in the city: Measured in thousands of dollars Ads: Average number of ads run in stores for that city during that month. Price of a substitute product: measured in dollars Population of the city: measured in thousands of people The dataset is on Canvas and, using Excel or any other statistical software, please answer the following questions: 1. Describe the patterns in quantity sold and own and rival prices during this time period using basic descriptive statistics. Graphs are welcome as well. 2. Take the logs of the variables, and estimate the demand function. a. Interpret the R-square. b. Interpret the coefficients for logP and logPsub c. Interpret the p-values associated with each independent…
1. Instruction: For each of the following variables, indicate whether it is qualitative or quantitative. For quantitative variables, further categorize them into the discrete or continuous type. (a) Gender (b) Hospital bed capacity. (c) Blood glucose level (in mg/100 mL) (d) Systolic blood pressure (e) Height (in centimeter) (f) Blood type (g) Per capita income (h) Household size (i) Mid-upper arm circumference (in centimeter) () Region (k) Pulse rate (I) Civil status
The bacterium Staphylococcus aureus is commonly found on the skin and rarely causes major problems. If it gets under the skin or into the lungs it can cause boils or pneumonia. If the strain of bacterium causing these problems is resistant to methicillin, the infections can be life threatening. Methicillin resistant Staphy- lococcus aureus or MRSA is, therefore, a major concern in hospitals and clinics. Given the death rate from MRSA lung infections is 20%, if 20 patients are admitted in the hospital find the following probabilities: (a) Less than 3 die (b) At least 3 die. (c) Between 6 and 3 die.
Can I have step by steo instructions to do this in excel? Thank you
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2. To investigate the effect of pH and catalyst concentration on product viscosity (sSt). Two levels of pH were used 5.6 and 5.9 and two catalyst concentration 2.5 and 2.7. Four products were tested with each combination of pH and catalyst. a. Use the estimate table below to test for main effects and interaction using a = 0.05. What are your conclusions? Predictor Constant Coefficient SDCoeff 191.563 165.49 pH 2.937 1.158 2.52 Catalyst -0.062 1.158 -0.05 pH*Catalyst 5.812 1.158 5.02 b. What is the value for the overall average viscosity? c. Write the regression model for this experiment. d. Below the interaction plot for the experiment. Discuss the information provided by the plot. To maximize viscosity what would be the recommended setting? Interaction Plot for Viscosity Data Mears 200 195 190- 185 Catalyst Concentration Mean Product Viscosity (cSt)
Algal blooms can have negative effects on an ecosystem by dominating its phytoplankton communities. Gonyostomum semen is a nuisance alga infesting many parts of northern Europe. Could the overall biomass of G. semen be controlled by grazing zooplankton species? A research team examined the relationship between the net growth rate of G. semen and the number of Daphnia magna grazers introduced in test tubes. Net growth rate was computed by comparing the initial and ﬁnal abundance of G. semen in the experiment, with a negative value indicative of a decrease in abundance. The table contains the findings. Number of D. magnagrazers 1 2 3 4 5 6 Net growth rate of G. semen -1.9 -2.5 -2.2 -3.9 -4.1 -4.3 Find the correlation, ?. Use decimal notation. (Enter your answer rounded to three decimal places.)
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