best automatic pool cleaner on the market image
bucs
i have a side suction that uses a skimmer. It is a concrete underground pool
Answer
First off I need more info. Is your pool equipped with an automatic pool cleaner line? Does it have a booster pump to propel a cleaner? Let me clarify. Automatic cleaners fall into two categories. Suction side and pressure side. Suction side cleaners operate off the filter pumps suction. Typically they plug into a skimmer, thereby diverting the skimming action to operate the cleaner. There are any number of these on the market. Which is best depends on several factors. Is your pool inground gunite (concrete) or vinyl? What type of debris gets in the pool THE MOST? (Leaves, sand, grass clippings, etc.)
Pressure side cleaners operate from the pressure (return) side. They either must have a dedicated pool cleaner line (installed when the pool is built) or work off a return fitting. Some cleaners require a separate booster pump to drive them, others do not. Again we need to know if the pool is gunite or vinyl and what type of debris is most prevalent. Answer these questions and I can direct you to the cleaner line I've had the most reliable service from. (Been in the pool business 35 years, so I've seen more than a few cleaners!.)
First off I need more info. Is your pool equipped with an automatic pool cleaner line? Does it have a booster pump to propel a cleaner? Let me clarify. Automatic cleaners fall into two categories. Suction side and pressure side. Suction side cleaners operate off the filter pumps suction. Typically they plug into a skimmer, thereby diverting the skimming action to operate the cleaner. There are any number of these on the market. Which is best depends on several factors. Is your pool inground gunite (concrete) or vinyl? What type of debris gets in the pool THE MOST? (Leaves, sand, grass clippings, etc.)
Pressure side cleaners operate from the pressure (return) side. They either must have a dedicated pool cleaner line (installed when the pool is built) or work off a return fitting. Some cleaners require a separate booster pump to drive them, others do not. Again we need to know if the pool is gunite or vinyl and what type of debris is most prevalent. Answer these questions and I can direct you to the cleaner line I've had the most reliable service from. (Been in the pool business 35 years, so I've seen more than a few cleaners!.)
Regression Problem- Confim my Anwers Please?
sabunabu
Please see the below and my answers-- please let me know if you disagree and also if you know the answers to the 2 questions I don't. Any help is greatly appreciated.
PoolVac, Inc. manufactures and sells a single product called the âSting Ray,â which is a patent-protected automatic cleaning device for swimming pools. PoolVacâs Sting Ray accounts for 65 percent of total industry sales of automatic pool cleaners. Its closest competitor, Howard Industries, has captured 18 percent of the market.
Using the last 26 months of its sales data, PoolVac wishes to estimate demand for its Sting Ray. Demand for Sting Rays is specified to be a linear function of its price (P), average income for households that have swimming pools in the U.S (MAVG) and the price of the competing pool cleaner sold by Howard Industries (PH). The general linear form of the demand function
Qd = a + b P + c MAVG + d PH.
The attached computer printout presents the regression output from 26 observations (monthly data) on the price charged for a Sting Ray (P), average income of households with pools (MAVG), and the price Howard industries charged for its pool cleaner (PH).
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The printout of part of regression output from Minitab for the empirical demand is below:
Regression Analysis: Q versus P, MAVG, PH
Predictor Coef SE Coef T P
Constant 2728.8 531.7 5.13 0.000
P -10.758 1.330 -8.09 0.000
MAVG 0.021420 0.009452 2.27 0.034
PH 3.166 1.344 2.36 0.028
S = 73.0546 R-Sq = 96.6% R-Sq(adj) = 96.2%
Analysis of Variance
Source DF SS MS F P
Regression 3 3379846 1126615 211.10 0.000
Residual Error 22 117414 5337
Total 25 3497260
Source DF Seq SS
P 1 3327368
MAVG 1 22878
PH 1 29600
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1. An estimated demand equation for PoolVac is:
Qd = 2728.8-10.758P+0.021420M+3.166Ph
2. Evaluate the statistical significance of the three estimated slope parameters using a significance level of .05 or 5 percent (you can either use p-values or do a t-test).Please, explain how you decided each parameter was statistically significant or not.
Since the P values of all 3 variables are within the 5% confidence interval, each variable should be considered as staristically significant in determining the demand of the pool vacuums.
3. What is the exact level of statistical significance for estimated slope parameters on price, average income of household and price of related good? Please, explain how you know.
We should look at the P value for each of the slope parameters and in doing so, we find that price is 100% significant, average income (Mavg) is 96.6% (100-.034) and price of competition (Ph) is 97.2% significant (100-.028).
4. Discuss the appropriateness and/or interpretations of the algebraic signs of the three slope parameters, based on your theoretical expectations. Interpret the numerical values of the three slope parameters in the context of this regression.
5. Now evaluate the overall fit of the estimated (sample) regression equation to the data.
a. What percentage of variability in Qd (linear) is explained by a model? Does it indicate a good overall fit? Please, explain.
b. Verify whether the overall regression equation is statistically significant, another words, verify the goodness of overall fit .What is the exact level of significance for the entire regression equation?
Looking at the F stat which is 211.1, we can say the overall regression equation is significant since the absolute value is large. Also, the P value is 0 so there is no chance that this regression equation doesnât explain the relationship between the given variables and quantity demanded.
Answer
All of your answers are good. To say that the F statistic has a large absolute value is a little vague; one would generally either consult an F table to the appropriate threshold value or just look at the P value in the computer output. On the other hand, it isn't wrong, and if your instructor taught it that way you should leave it in.
Regarding the questions you haven't answered, number 4 refers to the direction of the effects on your dependent variable that come with changes in the independent variables. You should look at your coefficients and consider what would happen if you changed the values in your variables. For example, if the price of the product goes up, demand for the product goes down because of the negative coefficient associated with the price variable. If this seems confusing, try plugging in some different values into the equation and calculating the result. The negative coefficient makes sense, because people are going to be less interested in buying something if its more expensive. The question is asking you to evaluate both the actual effects on demand and the expected effects for each of the variables.
Question 5a refers to the R-squared statistic (R-Sq), which is the percent of explained variability as mentioned in the question. Yours is quite high.
All of your answers are good. To say that the F statistic has a large absolute value is a little vague; one would generally either consult an F table to the appropriate threshold value or just look at the P value in the computer output. On the other hand, it isn't wrong, and if your instructor taught it that way you should leave it in.
Regarding the questions you haven't answered, number 4 refers to the direction of the effects on your dependent variable that come with changes in the independent variables. You should look at your coefficients and consider what would happen if you changed the values in your variables. For example, if the price of the product goes up, demand for the product goes down because of the negative coefficient associated with the price variable. If this seems confusing, try plugging in some different values into the equation and calculating the result. The negative coefficient makes sense, because people are going to be less interested in buying something if its more expensive. The question is asking you to evaluate both the actual effects on demand and the expected effects for each of the variables.
Question 5a refers to the R-squared statistic (R-Sq), which is the percent of explained variability as mentioned in the question. Yours is quite high.
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