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Enzymes are affected by both pH and?
Enzymes are affected by both pH and temperature. Changes in pH can alter the shape and charge distribution of the enzyme, affecting its ability to bind to substrate molecules and catalyze reactions. Extreme pH levels can denature the enzyme and render it nonfunctional.
What are extreme values?
There really isn't a rigorous definition, except that they are beyond the usual range of the data. To some it may be a value (or range of values) that could occur 1:50 times, to others it might be 1:1000 or 1:10000 times. It may be a very high number or a very low number, but it must be a number whose occurrence is rare.
What is the Latin word for extreme?
The Latin word for extreme is "extremus."
How do find lower and upper extreme?
To find the lower extreme, you need to identify the smallest value in a data set. To find the upper extreme, you need to identify the largest value in the data set. These values represent the lowest and highest points of the data distribution.
The ability of an enzyme to catalyze a reaction is not affected by?
The ability of an enzyme to catalyze a reaction is not affected by changes in temperature or pH within a certain range known as the enzyme's optimal conditions. However, extreme changes in temperature, pH, or enzyme concentration can denature the enzyme and affect its activity. Additionally, the substrate concentration can affect the rate of reaction up to a point of saturation, where all enzyme active sites are occupied.
Which of the following is least affected if an extreme high outlier is added to your data mean median or standard deviation or ALL?
The median is least affected by an extreme outlier. Mean and standard deviation ARE affected by extreme outliers.
What measures of central location is affected most by extreme values?
The mean is most affected. Mode and Median are not influenced as much by outliers.
What is the least resistant to outliers mean median or mode?
The mean is the least resistant to outliers because it is influenced by every value in the dataset, including extreme values. In contrast, the median, which represents the middle value, is less affected by outliers, as it depends only on the order of the data. The mode, being the most frequently occurring value, is also generally unaffected by outliers. Thus, in terms of sensitivity to extreme values, the mean is the most vulnerable.
Is the variance impacted by extreme outliers?
Yes, it is.
Is the mean a better measure of location when there are no outliers?
Yes, the mean is generally a better measure of central tendency when there are no outliers, as it takes into account all values in the dataset and provides a mathematically precise average. In the absence of outliers, the mean reflects the true center of the data distribution effectively. However, in the presence of outliers, the median might be preferred since it is less affected by extreme values.
Which measure of central tendency is most influenced by outliers?
The mean is the measure of central tendency most influenced by outliers. Since it is calculated by summing all values and dividing by the number of values, extreme values can significantly skew the result. In contrast, the median and mode are less affected by outliers, making them more robust measures in such situations.
Disadvantages of the mean in statistics?
the mean is affected by outliers
Is absolute mean deviation affected by outliers?
Yes.
What is the effect of extreme value on mean?
Outliers pull the mean in the direction of the outlier.
When is the mean used as a measure of central tendency?
When there aren't extreme values (outliers)
Why calculate for the mean and median in relation to a sample?
Both the mean and median represent the center of a distribution. Calculating the mean is easier, but may be more affected by outliers or extreme values. The median is more robust.
Extreme numbers compared to the rest of the data are called?
Extreme numbers in the data as compared the the rest of the data are called OUTLIERS.
