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Use the Kolmogorov Smirnoff goodness-of-fit test.
A normal distribution is a bell shaped curve, which is nearly symmetrica. It looks like an upside down bell. It can be squished low (platykurtic) or pulled high and skinny (leptokurtic) but it is still bell shaped and symmetrical.
A mathematical test is to use the pearson's skew. If the pearson's skew is between 0 and 0.49, then the data is a non-problematic or normally distributed. If it is greater than 0.50, then it is not a normal distribution so one cannot treat it as such.
The pearson's skew equation is
skew p= (3 (mean - median)) / (SD(x) SD(y))
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Differeciate between mode mean and median?
All three are measures of distribution. they hep us understand the distribution of a series of data points. or otherwise said, if you had to guess what something was and you had a whole bunch of estimates, what is the best guess. If the data has a couple spikes (a modal distribution) say there were a few ones, a couple twos, a whole bunch of threes, a few fours, a whole bunch of fives, and a few sixes, than the graph would spike at three and five. To generate a best guess from a set of data that is "modal" you use the "mode". If the data is non-modal but leans toward one end or the other. Say a lot of ones, a lot of twos, good number of threes, some fours, some fives, we'd say this data is "skewed". The best guess for a skewed distribution of data is going to be the median which is the mathematical middle point in a rank order list of data points. If the data was "normally distributed" or had a few ones, few more twos, bunch of threes, few less fours, and only a few fives than we'd say the data was normally distributed, or a "bell curve". In the case of normally distributed data the mean is your best measure. all three are averages. all three describe a collection of data. Which of the three best describes the data depends on the data distribution.
Why is it that only one normal distribution table is needed to find any probability under the normal curve?
Anything that is normally distributed has certain properties. One is that the bulk of scores will be near the mean and the farther from the mean you are, the less common the score. Specifically, about 68% of anything that is normally distributed falls within one standard deviation of the mean. That means that 68% of IQ scores fall between 85 and 115 (the mean being 100 and standard deviation being 15) AND 68% of adult male heights fall between 65 and 75 inches (the mean being 70 and I am estimating a standard deviation of 5). Basically, even though the means and standard deviations change, something that is normally distributed will keep these probabilities (relative to the mean and standard deviation). By standardizing these numbers (changing the mean to 0 and the standard deviation to 1) we can use one table to find the probabilities for anything that is normally distributed.
The annual precipitation for one city is normally distributed with mean of 38.9 inches and a standard deviation of 3.3 inches Find the 20th percentile?
45.665 inches Type your answer here... what is the answer??
What does one use a bandwidth calculator for?
One would use a bandwidth calculator to see how much data that they are using. Normally it goes by month long periods and you could measure it by that standard.
What is the average of 48 and 67?
Normally, at least two numbers are used to determine an average. If there is only one number, then the average is the number itself, so the answer is 48.
Difference between database and distributed database?
A database is a collection of related data organized for quick search and retrieval, usually stored on a single computer system. A distributed database is a database in which parts of the database are stored in multiple locations but managed by a centralized control. Distributed databases are used to improve performance, reliability, and scalability by allowing data to be spread across multiple servers or locations.
What are distributed-databases in dbms?
Distributed databases in a DBMS are databases that are stored on multiple computers across a network. They allow for data to be spread out and accessed simultaneously from different locations, which can improve performance and scalability. Distributed databases can enhance fault tolerance and reduce the risk of data loss.
If data are normally distributed does the range give you a rough idea about the standard deviation of the sample?
Yes, the range gives you an idea of the S.D. Assuming that the largest and smallest data points are not "outliers," a set of data with a wide range will have a greater S.D. than a set with a narrow one.
Why the sample should be normally distributed?
The sample should not be normally distributed.If you have a population of size N from which a random sample of size n is to be drawn, then there are NCn possible samples. Each one of these must have the same probability of being thesample. That is, the sample is uniformly distributed - not Normally.
Assumption of one-way analysis of variance?
The results of a one-way ANOVA can be considered reliable as long as the following as The results of a one-way ANOVA can be considered reliable as long as the following assumptions are met: * Response variable must be normally distributed (or approximately normally distributed). * Samples are independent. * Variances of populations are equal. * The sample is a Simple Random Sample (SRS). ANOVA is a relatively robust procedure with respect to violations of the normality assumption (Kirk, 1995) If data are ordinal, a non-parametric alternative to this test should be used - Kruskal-Wallis one-way analysis of variance. sumptions are met: * Response variable must be normally distributed (or approximately normally distributed). * Samples are independent. * Variances of populations are equal. * The sample is a Simple Random Sample (SRS). ANOVA is a relatively robust procedure with respect to violations of the normality assumption (Kirk, 1995) If data are ordinal, a non-parametric alternative to this test should be used - Kruskal-Wallis one-way analysis of variance
What is centralized database?
Distributed and Centralized Databases Distributed data is defined as collection of logically distributed database which are connected with each other through a network. A distributed database management system is used for managing distributed database. Each side has its own database and operating system.A centralized database has all its data on one place. As it is totally different from distributed database which has data on different places. In centralized database as all the data reside on one place so problem of bottle-neck can occur, and data availability is not efficient as in distributed database. Let me define some advantages of distributed database, it will clear the difference between centralized and distributed database.Users can issue commands from any location to access data and it does not affect the working of database. Distributed database allows us to store one copy of data at different locations. Its advantage is that if a user wants to access data then the nearest site (location) will provide data so it takes less time.There are multiple sites (computers) in a distributed database so if one site fails then system will not be useless, because other sites can do their job because as I earlier said that same copy of data is installed on every location. You will not find this thing in centralized database.Any time new nodes (computers) can be added to the network without any difficulty.Users do not know about the physical storage of data and it is known as distribution transparency, as we know that ideally, a DBMS must not show the details of where each file is stored or we can say that a DBMS should be distribution transparent.
What is the importance of a distributed database?
A distributed database enhances scalability and fault tolerance by spreading data across multiple nodes. It improves performance by allowing for parallel processing of queries. It also increases data availability and reduces the risk of data loss in case of system failures.
What is the approximate percentage score of less than 140 using the 68-95-99.7 rule if a set of test scores is normally distributed with a mean of 100 and a standard deviation of 20?
The 68-95-99.7 rule states that in a normally distributed set of data, approximately 68% of all observations lie within one standard deviation either side of the mean, 95% lie within two standard deviations and 99.7% lie within three standard deviations.Or looking at it cumulatively:0.15% of the data lie below the mean minus three standard deviations2.5% of the data lie below the mean minus two standard deviations16% of the data lie below the mean minus one standard deviation50 % of the data lie below the mean84 % of the data lie below the mean plus one standard deviation97.5% of the data lie below the mean plus two standard deviations99.85% of the data lie below the mean plus three standard deviationsA normally distributed set of data with mean 100 and standard deviation of 20 means that a score of 140 lies two standard deviations above the mean. Hence approximately 97.5% of all observations are less than 140.
The percentage that is one standard deviation away from mean?
For normally distributed data. One standard deviation (1σ)Percentage within this confidence interval68.2689492% (68.3% )Percentage outside this confidence interval31.7310508% (31.7% )Ratio outside this confidence interval1 / 3.1514871 (1 / 3.15)
What are some causes of skewed data distributions?
The cause of skewed data distributions are extreme values, also know as outliers. For example imagine taking the weights of people you see on the street. If you have 9 cheerleaders' weights and then the weight of a sumo wrestler mixed into the averages this skews the data. This makes the mean much higher because of the one extreme value. Instead of the data being distributed normally, it is distributed with a positive skew. If there is a really small extreme value instead of a really large one, then the data has a negative skew. This could be the heights of people on the street, but one of them would be a midget. The mean is made lower by that one extreme value. Perhaps, little person is a more politically correct term in our day.
What percentage of the normally distributed population lies within the plus or minus one standard deviation of the population mean?
68.2%
What is a distributed system?
In computing, a distributed system is a system that works in different locations or work using separate processing or processors to their jobs, often simultaneously. Data can be stored in different locations in a distributed database, although a user won't know it. The data will appear on their screen when they access, so they are unaware of its location. Networks use distributed systems to link up systems that work together but are in separate locations. If there are full copies of data in various locations, then if one location gets damaged or inaccessible, the system can still function. This makes data and systems more secure.
