From largest to smallest, the seven classification are: 1.Kingdom
2.Phylum
3.Class
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4.Order
5.Family
6.Genus
7.Species
So species is the smallest
Answer:
P generation: 1 purple flower (AA) : 1 white flower (aa)
F1 generation: 4 purple flowers (Aa) : 0 white flowers
F2 generation: 3 purple flowers (AA, Aa) : 1 white flower
Explanation:
Assuming the parents are AA and aa, the allele for white flowers is recessive, so there needs to be two of them for the trait to be expressed. Thus, the capital A purple allele that the other parent contributes will mask that white allele and all the flowers will appear purple. However, all of the offspring are Aa now, so when they are crossed, there's a 25% chance that they'll both contribute the lowercase a allele that codes for white flowers. Remember that if both of them give the lowercase a allele then the offspring will be aa and appear white.
Answer Migration, in turn, covers both immigration and emigration. Another key difference is, immigration is permanent while migration doesn’t have to be. People who travel and stay in a country for a few months — for instance, because of a seasonal job they have — are also called migrants.
Explanation:
Answer & Explanation:
First, correlation and causation both need an independent and dependent variable. An independent variable is a condition or piece of data in an experiment that can be controlled or changed. A dependent variable is a condition or piece of data in an experiment that is controlled or influenced by an outside factor, most often the independent variable.
If there is a correlation, then sometimes we can assume that the dependent variable changes solely because the independent variables change. This is where the debate between correlation and causation occurs. However, there is a difference between cause and effect (causation) and relationship (correlation). Sometimes these areas can be confused and muddled when analyzing data.
- You probably know that a correlation is the relationship between two sets of variables used to describe or predict information. There is an emphasis here on relationship. Sometimes we can use correlation to find causality, but not always. Remember that correlation can either be positive or negative.
A positive correlation, where the dependent variables and independent variables in a data set increase or decrease together. If the numbers sloped downward, then you have a data set with a negative correlation, where the dependent variables and independent variables in a data set either increase or decrease opposite from one another.
Whilst a negative correlation means if the independent variables decrease, then the dependent variable would increase, and vice versa.
- Causation, also known as cause and effect, is when an observed event or action appears to have caused a second event or action. For example, I bought a brand new bed comforter and placed it in my washing machine to be cleaned. After cleaning the comforter, my washing machine stopped working. I may assume that the first action, washing the comforter, caused the second action, broken washing machine.
<em>I hope this helped! :)</em>
