how to analyze fgd data?
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Transcribe all of the focus group comments. If you do more than one focus group, rearrange the comments so that you have answers together for each interview protocol question. For each question, note the main ideas that occur in the answers. Review the main ideas to identify ideas which occur again and again.
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['Data and its Frequency Distribution.', 'Pictographs.', 'Bar Graphs.', 'Histogram and Pie-Charts.', 'Chance and Probability.', 'Arithmetic Mean.', 'Median and Mode.']
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['Calculate the mean or average of each data set. ... ', 'Subtract the deviance of each piece of data by subtracting the mean from each number. ... ', 'Square each of the deviations.', 'Add up all of the squared deviations.', 'Divide this number by one less than the number of items in the data set.']
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['Calculate the mean (x̅) of a set of data\u200b', 'Subtract the mean from each point of data to determine (x-x̅). ... ', 'Square each of the resulting numbers to determine (x-x̅)^2. ... ', 'Add the values from the previous step together to get ∑(x-x̅)^2.']
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To find FV, you must first identify PV, the interest rate, and the number of periods from the present to the future. The interest rate and the number of periods must have consistent units. If one period is one year, the interest rate must be X% per year, and vis versa.
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FWHM can be determined as the distance between the curve points at the peak half maximum level. On a data graph, draw a vertical line from the peak maximum to the baseline. Measure the length of this line and divide it by 2 to find the center of the line.
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Fgrav = m*g where d represents the distance from the center of the object to the center of the earth. In the first equation above, g is referred to as the acceleration of gravity. Its value is 9.8 m/s2 on Earth. That is to say, the acceleration of gravity on the surface of the earth at sea level is 9.8 m/s2.
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Remember, you count frequencies. To find the relative frequency, divide the frequency by the total number of data values. To find the cumulative relative frequency, add all of the previous relative frequencies to the relative frequency for the current row.
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['Consider each particle you have in turn. ... ', 'Divide your total count by N, the number of reference particles you considered -- probably the total number of particles in your data.', 'Divide this number by 4 pi r^2 dr, the volume of the spherical shell (the surface area 4 pi r^2, multiplied by the small thickness dr).']
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Texture Analysis Using the Gray-Level Co-Occurrence Matrix (GLCM) ... The GLCM functions characterize the texture of an image by calculating how often pairs of pixel with specific values and in a specified spatial relationship occur in an image, creating a GLCM, and then extracting statistical measures from this matrix.
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['Moving average (MA)', 'Exponential moving average (EMA)', 'Stochastic oscillator.', 'Moving average convergence divergence (MACD)', 'Bollinger bands.', 'Relative strength index (RSI)', 'Fibonacci retracement.', 'Ichimoku cloud.']
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['Relation: A B C D E F G H I J K L M Functional dependencies: A -> B C D E E -> F G H I -> J         A I -> K A L -> M.', 'First: Find all keys. ... ', 'Check R for BCNF condition: ... ', 'Decompose: ... ', 'Check R1 for BCNF condition: ... ', 'Decompose: ... ', 'Check R11 for BCNF condition: ... ', 'Check R12 for BCNF condition:']
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['Calculate the mean of your data set.', 'Subtract that mean from each of the scores in your data set to determine the individual deviation of each score from the mean.', 'Square each of those individual deviations.', 'Sum all of the squared deviations.', 'Divide that sum by one less than the sample size (N–1)']
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defg is a parallelogram with GH perpendicular DE . if GH =10cm and GF=12cmfind area(triangle GEF)and area(DEFG)
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['Get the mass of each element by assuming a certain overall mass for the sample (100 g is a good mass to assume when working with percentages). ... ', 'Convert the mass of each element to moles. ... ', 'Find the ratio of the moles of each element. ... ', 'Use the mole ratio to write the empirical fomula.']
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Methods for time series analysis may be divided into two classes: frequency-domain methods and time-domain methods. The former include spectral analysis and wavelet analysis; the latter include auto-correlation and cross-correlation analysis.
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['Go to the data table.', 'Click analyze.', 'If you have a XY or Grouped table: Choose "Row means/totals". If you have a column table: Choose "Column statistics".', 'Choose options on the dialog and click OK.']