It is the number of observations that might be expected for a particular category if the [null] hypothesis that is being tested is true.
It enables us to tell the difference between observed and expected frequencies objectively as it is practically impossible to tell the difference just by looking at the data.
This is concerned with frequency. Can be used to test whether the observed frequencies in a particular case differ significantly from those which would be expected in the null hypothesis. source: analysis related lectures
The plural of frequency is frequencies. As in "radio waves travel on different frequencies".
Absolute frequencies are calculated by first identifying intervals based on your data and then identifying the number of values within your data set that lie within these interval. Relative frequencies divide the absolute frequencues by the number of values in the set. It is a good practice to provide the absolute frequencies, perhaps in a bar chart of relative frequencies as a number above each bar.
No it is not. The ogive is a graph that represents the cumulative frequencies for the classes in a frequency distribution.
The maximum likelihood estimate under the null hypothesis gives the best estimate for expected frequencies.
You first decide on a null hypothesis. Expected frequencies are calculated on the basis of the null hypothesis, that is, assuming that the null hypothesis is true.
The longest wavelengths are usually referred to as radio waves, whereas the highest frequencies are referred to as cosmic rays (the opposite end of the spectrum).
Sound quality is the term for the bending of overlapping sound wave frequencies through interference.
Expected frequencies are used in a chi-squared "goodness-of-fit" test. there is a hypothesis that is being tested and, under that hypothesis, the random variable would have a certain distribution. The expected frequency for a "cell" is the number of observations that you would expect to find in that cell if the hypothesis were true.
Adventitious is one medical term meaning not expected.
The null hypothesis in a chi-square goodness-of-fit test states that the sample of observed frequencies supports the claim about the expected frequencies. So the bigger the the calculated chi-square value is, the more likely the sample does not conform the expected frequencies, and therefore you would reject the null hypothesis. So the short answer is, REJECT!
Inaudible sounds are sounds that you cannot hear. Audible sounds are sounds that you can hear. Frequencies capable of being heard by humans are called audio or sonic. The range is typically considered to be between 20Hz and 20,000Hz.[3] Frequencies higher than audio are referred to as ultrasonic, while frequencies below audio are referred to as infrasonic
Materials which do not allow the transmission of light are called opaque. These substances have chemical compositions, some of which are referred to as absorption centers. This means that the material absorbs all of the light wave frequencies, not just some while reflecting other frequencies.
The chi-square test is used to analyze a contingency table consisting of rows and columns to determine if the observed cell frequencies differ significantly from the expected frequencies.
The way you are expected to act by others is referred to as etiquette or manners.
the frequencies found in the sample data