Rf is a value that is usually seen in chromatography (such as thin-layer chromatography, or TLC). It is a measure of how far the compound has traveled along the stationary phase. This distance is affected by the compounds affinity to the stationary phase (the TLC plate) and its affinity to the mobile phase (the solvent). Generally this directly relates to the polarity of the compound, but other factors may influence this.
Since similar compounds (in structure) also have similar dipole moments (polarity), similar compounds will typically have similar Rf values. However, there are exceptions and compounds that have different functional groups can end up having similar polarities and thus similar Rf values. TLC is usually used as an initial measure of identification. If the Rf of the reference matches the Rf of the unknown, it is likely the compounds are the same, but further investigation with other analytical techniques is necessary to confirm this.
No, two sets of scores with the same mean are not necessarily identical. The scores could differ in terms of their distribution, range, variability, and individual values even though they have the same mean.
By the same amount of DNA, fragments of the same size and the same DNA molecules. WRONG The real answer on the people who have multiple choice or e2020 It would be "all the above"
If you mean meiosis I and meiosis II, then no they are not identical, but meiosis II does follow meiosis I.
Sorry we do not know what you mean by "eater molecules".
Molecular means relating to molecules.
No. The molecules MAY (and probably are if you are presented with this situation in school/college lab courses) be identical but just the Rf values is not enough information to determine, you must conduct additional tests. Two different molecules can have the same Rf value.Compound A will always have an Rf of X in solvent M. Compound B will always have and Rf of Y in solvent M. But, Rf X can be equivalent to Rf Y without compounds A and B being identical.
Data from random samples will not always include the same values. Values are chosen randomly and they may or may not be the same. So means will vary among random samples.
for a normal-shaped distribution with n=50 and siqma =8 : a- what proportion of the scores have values between 46 and 54? b- for samples of n= 4, what means have values what proportion of the sample mean have values between 46 and 54? c- for samples of n= 16, what means have values what proportion of the sample mean have values between 46 and 54?
It means that there are is no variation from the mean. In other words, all values in your sample are identical.
You need to add all the values shown on the histogram and then divide that sum by the number of values (samples). Example: There are 5 values: A, B, C, D, E. Mean value is: (A+B+C+D+E) / 5
No, two sets of scores with the same mean are not necessarily identical. The scores could differ in terms of their distribution, range, variability, and individual values even though they have the same mean.
The answer depends on the population and is described by the sampling distribution of the mean.
Variance = 0 means they are all the same. So the question is simplified to: what 5 identical values have a mean of 20. Since they are identical, their mean value is the same as themselves. So the answer, trivially, is [20, 20, 20, 20, 20].
A sample with a standard deviation of zero indicates that all the values in that sample are identical; there is no variation among them. This means that every observation is the same, resulting in no spread or dispersion in the data. Consequently, the mean of the sample will equal the individual values, as there is no deviation from that mean.
The weighted arithmetic mean is used, if one wants to combine average values from samples of the same population with different sample sizes: : The weights wi represent the bounds of the partial sample. In other applications they represent a measure for the reliability of the influence upon the mean by respective values. rhinostar
identities mean who you are
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