Frequencies A sound wave is created as a result of a vibrating object. The object that is vibrating‚ is the source of the disturbance that moves throughout the medium. The object creating the disturbance could be the vocal cords of a person‚ the vibrating strings and soundboard on a string instrument‚ or the vibrating diaphragm of a radio speaker. If an object has the ability to vibrate‚ then it will produce sound. Almost every
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Relative frequency of a category = Frequency of that category Sum of all frequencies Class width = Upper boundary– Lower boundary Class midpoint or mark = Lower limit+ Upper limit/2 Approximate class width=Largest value -mallest value / Number of classes Relative frequency of a class=Frequency of that class/Sum of all frequencies Cumulative relative frequency=Cumulative frequency of a class/Total observations in the data set Mean = Average ‚ Median ‚ Mode Range = Largest value–
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FREQUENCY DISTRIBUTION WHAT IT IS Frequency distributions summarize and compress data by grouping it into classes and recording how many data points fall into each class. That is‚ they show how many observations on a given variable have a particular attribute. For example‚ a survey is taken of 50 people’s favorite color. The frequency distribution might indicate 15 people selected green‚ 12 blue‚ 6 red‚ 7 yellow‚ and 10 purple. Converting these raw numbers into percentages would then provide an
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FREQUENCY POLYGONS W H AT I S A F R E Q U E N C Y P O LY G O N Frequency polygons are a graphical device for understanding the shapes of distributions. They serve the same purpose as histograms‚ but are especially helpful for comparing sets of data. Frequency polygons are also a good choice for displaying cumulative frequency distributions. H O W T O C R E AT E A F R E Q U E N C Y P O LY G O N To create a frequency polygon‚ start just as for histograms‚ by choosing a class interval. Then draw
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Allele Frequencies in Populations: Hardy-Weinberg Law Assumptions Already Made (Can’t Control) 1) Population Size 2) Mutation 3) Natural Selection 4) Immigration/emmigration 5) Non-random mate choice Can Control 1) Population Size 2) Natural Selection Control Variable Left side Experimental Variable Right Side Comparisons are most meaningful when there is only ONE difference between populations For this experiment only the population size should be different and everything else should
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of 15. Use the 68-95-99 rule to find the following quantities: a. Percentage of rates less than 70 = 50% b. Percentage of rates less than 55 = 16% c. Relative frequency of rates less than 40 = 2.5% d. Percentage of rates less than 85 = 84% e. Relative frequency of rates less than 100 = 97.5% f. Percentage of rates greater than 85 = 16% g. Percentage of rates greater than 55 = 84% h. Relative frequency of rates
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Frequency Distribution (A) Introduction 1. Ungrouped data versus grouped data Ungrouped data (Raw data): It is a list of individual observed values of the random variable Grouped data (a frequency distribution): It is a table that displays the data in grouping along with the number of occurrences that fall into each group. 2. The components of a frequency distribution a. Class limits: They identify the inclusive values in a class of a frequency distribution The
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Understanding LNB Frequencies and Transponder Frequencies « on: April 01‚ 2008‚ 07:44:50 PM »http://www.galaxy-marketing.com/satellite-support-forum1/index.php?topic=39.0 | | These are LNB types and frequencies: DSS Circular LNB = 12.2GHz-12.7GHz Standard FSS Linear LNB = 11.7GHz-12.2GHz Universal FSS Linear LNB = 10.7GHz-12.7GHz Keeping the above frequency range in mind‚ now let’s look at the frequency ranges of your transponder. Keep in mind that the transponder frequencies are presented
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Statistics: • Science of gathering‚ analyzing‚ interpreting‚ and presenting data • Measurement taken on a sample • Type of distribution being used to analyze data Descriptive statistics: Using data gathered on a group to describe or reach conclusions about that same group only. Descriptive statistics are the tabular‚ graphical‚ and numerical methods used to summarize data. Collect‚ organize‚ summarize‚ display‚ analyze Eg: According to Consumer Reports‚ General Electric washing machine
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signals‚ are “high-leverage” components in that even very small deviations from ideal in their behavior can lead to large degradations in overall system performance. Therefore‚ successful simulation of wireless communication systems depends upon the use of modulator models that capture all of the significant deviations from ideal behavior. In the “usual” development of data modulation techniques as presented in most communications texts‚ the various techniques are presented in order of complexity
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