An important factor in solid missile fuel is the particle size distribution. Significant problems occur if the particle sizes are too large. From production data in the past, it has been determined that the particle size (in micrometers) distribution is characterized by f(x) = { 3x-4, x>1 elsewhere (a) Verify that this is a valid pdf. (b) Find the cdf of X. (c) Find the average particle size in micrometers.

An important factor in solid missile fuel is the particle size distribution. Significant problems occur if the particle sizes are too large. From production data in the past, it has been determined that the particle size (in micrometers) distribution is characterized by f(x) = { 3x-4, x>1 elsewhere (a) Verify that this is a valid pdf. (b) Find the cdf of X. (c) Find the average particle size in micrometers.

Calculus For The Life Sciences

2nd Edition

ISBN:9780321964038

Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Chapter2: Exponential, Logarithmic, And Trigonometric Functions

Section2.CR: Chapter 2 Review

Problem 111CR: Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data...

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Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.
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A sales manager wants to examine the relationship between the number of daily customers (x) and the revenue generated (y). For this purpose, he made observations in a randomly chosen 6 days for a store and observed the number of daily customers and the revenue (1000 TL). The personally created data set for the x and y variables is included in the attached “Homework data” file. Using the data set defined on your behalf; x1 x2 x3 x4 x5 x6 y1 y2 y3 y4 y5 y6 sb1 Burak data 74 86 96 105 110 124 290 307 331 406 421 481 0.491 a) Create the regression equation b) Interpret b0 and b1 values c) Test and interpret whether there is a linear relationship between the number of daily customers and the income obtained at the level of α = 0.05 significance. Could you explain this question again and in more detail especially not in excel image
A sales manager wants to examine the relationship between the number of daily customers (x) and the revenue generated (y). For this purpose, he made observations in a randomly chosen 6 days for a store and observed the number of daily customers and the revenue (1000 TL). The personally created data set for the x and y variables is included in the attached “Homework data” file. Using the data set defined on your behalf; x1 x2 x3 x4 x5 x6 y1 y2 y3 y4 y5 y6 sb1 Burak data 74 86 96 105 110 124 290 307 331 406 421 481 0.491 a) Create the regression equation b) Interpret b0 and b1 values c) Test and interpret whether there is a linear relationship between the number of daily customers and the income obtained at the level of α = 0.05 significance. d) Establish and interpret the 95% confidence interval for β1.
a) We conduct a regression of size on hhinc, owner, hhsize, hhsize2,and hhsize3. We do not include the constant. The regression output is reported in Table 3. Would you conclude that the home size increases with the household size? Interpret the sign and magnitude of the estimated coefficients of hhsize1, hhsize2, and hhsize3.
A sales manager wants to examine the relationship between the number of daily customers (x) and the revenue generated (y). For this purpose, he made observations in a randomly chosen 6 days for a store and observed the number of daily customers and the revenue (1000 TL). The personally created data set for the x and y variables is included in the attached “Homework data” file. Using the data set defined on your behalf; x1 x2 x3 x4 x5 x6 y1 y2 y3 y4 y5 y6 sb1 Burak data 74 86 96 105 110 124 290 307 331 406 421 481 0.491 d) Establish and interpret the 95% confidence interval for β1.