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Oct 6, 2019 · Chapter 3 consists of three parts: (1) Purpose of the study and research design, (2) Methods, and (3) Statistical Data analysis procedure. Part one, Purpose of the study and Research Design,...
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Chapter 3 consists of three parts: (1) Purpose of the study...
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- The most common applications of statistical data treatment :
- Finding the confidence interval when is unknown
- Comparison of Two Experimental Means
- 7C Analysis of variance
- Determining Which Results Differ
- 2 MSE
- 7D Detection of gross errors
- The Q Test
- Other Statistical Tests
- Recommendations for Treating Outliers
Defining a numerical interval, the confidence interval, around the mean of a set of replicate results within which the population mean can be expected to lie with certain probability. This interval is related to the standard deviation of the mean. Determining the number of replicate measurements required to ensure that an experimental mean ...
In case of limitations in time or in the amount of sample available, a single set of replicate measurements must provide not only a mean but also an estimate of precision. s calculated from a small set of data may be quite uncertain. Thus, confidence intervals are necessarily broader when we must use a small sample value of s as our estimate of ...
In many cases, it needs to be determined whether a difference in the means of two sets of data is real or the result of random error. In some cases, the results of chemical analyses are used to determine whether two materials are identical. In other cases, the results are used to determine whether two analytical methods give the same values or ...
The methods used for multiple comparisons fall under the general category of analysis of variance, or ANOVA. These methods use a single test to determine whether there is or is not a difference among the population means rather than pair wise comparisons as is done with the t test. In case of a potential difference, multiple comparison procedur...
There are several methods to determine which means are significantly different. The least significant difference method is the simplest method in which a difference is calculated that is judged to be the smallest difference that is significant. The difference between each pair of means is then compared to the least significant difference to det...
N g where MSE is the mean square for error and the value of t has N – I degrees of freedom.
An outlier is a result that is quite different from the others in the data set. It is important to develop a criterion to decide whether to retain or reject the outlying data point. The choice of criterion for the rejection of a suspected result has its perils. If the standard is too strict so that it is quite difficult to reject a questionable...
The Q test is a simple, widely used statistical test for deciding whether a suspected result should be retained or rejected. In this test, the absolute value of the difference between the questionable result xq and its nearest neighbor xn is divided by the spread w of the entire set to give the quantity Q: x Q q n w The Q test for outliers
Statistical rules should be used with extreme caution when applied to samples containing only a few values. The only valid reason for rejecting a result from a small set of data is the sure knowledge that an error was made in the measurement process. Else, a cautious approach to rejection of an outlier is wise.
Reexamine carefully all data relating to the outlying result to see if a gross error could have affected its value. This recommendation demands a properly kept laboratory notebook containing careful notations of all observations. If possible, estimate the precision that can be reasonably expected from the procedure to be sure that the outlying resu...
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Statistics provide an objective approach to understanding and interpreting the behaviors that we observe and measure. Descriptive statistics are used to describe and summarize data. They include measures of central tendency (mean, median, mode) and measures of variability (range, variance, standard deviation).
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Appendix A ∙ Statistical treatment of data A‐7 and the number of years you go to school. Table A‐3 lists data collected by the United States Census Bureau on years of school attended by the head of a household and average household income; the
These memos support all activities of qualitative data analysis as suggested by Miles and Huberman (1994): data reduction (extracting the essence), data display (organiz-ing for meaning), and drawing conclusions (explaining the findings).
Statistical treatment of data . Including statistical analysis using Microsoft® Excel® . Mean and standard deviation . Suppose that we make N measurements of the same quantity x.
core topics in statistics before he gets to probability theory. These include: summarizing data; analyzing relationships be- tween variables; even regression analysis; and causality.
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