Two male mice, which we will call male a and male b, are both phenotypically normal. male a was from a litter that contained half phenotypically normal mice and half dwarf mice. the mother of male a was known to be homozygous for the normal igf2 allele. male b was from a litter of eight mice that were all phenotypically normal. the parents of male b were a phenotypically normal male and a dwarf female. male a and male b were put into a cage with two female mice that we will call female a and female b. female a is a dwarf and female b is phenotypically normal. the parents of these two females were unknown, although it was known that they were from the same litter. the mice were allowed to mate with each other, and the following data were obtained: female a gave birth to three dwarf babies and four normal babies. female b gave birth to four normal babies and two dwarf babies. which male(s)mated with female a and female b? male a with both females male a with female b, and male b with female a male a with female a, and male b with female b could not be determined male b with both females

Reject the null hypothesis that there is no difference between males and females on the recognition task.

Step-by-step explanation:

Use MS-Excel to compute the required values.

Consider the data for male subjects first:

Mean = SD = SEM =  

Consider the data for female subjects:

Mean = SD = SEM =  

Use the Data Analysis tool in Excel to perform the hypothesis test.

The hypothesis can be defined as follows:

H₀: There is no difference between the two responses, i.e. .

Hₐ: There is a significant difference between the two responses, i.e. .

Consider the Excel output for the hypothesis test.

The test statistic value is:

t = -5.32

The degrees of freedom is:

df = 38

The p value associated with the t value is:

p-value =  4.91025E-06  

As the p-value is less than the significance level the null hypothesis will be rejected.

Conclusion:

Reject the null hypothesis that there is no difference between males and females on the recognition task.

DNA makes RNA, which makes protein.

Hello there.

Eight people, female and male, were surveyed about their choice of car color, green or blue. The table shows the choices they made.

Which two-way table correctly compares the categorical data?

B. 
Green Blue 
Female 2 1 
Male 2 3 

Is this your homework?

Stamen is the male part and the femail part is called the pistil, and the stamen has anthers and filiments, the anthers carry pollen fyi. hope this and plz mark brainly

The two-way table correctly compares the categorical data would be the second choice or letter B:

Green Blue 
Female 2 1 
Male 2 3 

I hope my answer has come to your help. God bless and have a nice day ahead!

Two events are said to be independent of each other, when the probability that one event occurs in no way affects the probability of the other event occurring. For example, the outcome of rolling a die has no way of affecting the outcome of flipping a coin. Thus we say that both events are indipendent events.

In conditional probability, in the case where events A and B are independent, the conditional probability of event B given event A, P(B|A) is simply the probability of event B, that is P(B).

Recall that the conditional probability of event, say B given event, say A, P(B|A) is given by


Given the table
                                           Male      Female       Total
Income over $75,000          585          485          1,070
Income below $75,000        65            65            130
Total                                    650          550          1,200

P(being female | the person earns over $75,000) = P(Females that earns over $75,000) divided by P(people that earns over $75,000).

P(Females that earns over $75,000) =

P(people that earns over $75,000) =

Thus, P(being female | the person earns over $75,000) =

P(being female) =

Therefore, since P(being female | the person earns over $75,000) is not equal to P(being female), then "being female" and "earning over $75,000" are NOT independent events.

Therefore, the correct answer is
No, P(being female | the person earns over $75,000) ≠ P(being female)

Two events are said to be independent of each other, when the probability that one event occurs in no way affects the probability of the other event occurring. For example, the outcome of rolling a die has no way of affecting the outcome of flipping a coin. Thus we say that both events are indipendent events.

In conditional probability, in the case where events A and B are independent, the conditional probability of event B given event A, P(B|A) is simply the probability of event B, that is P(B).

Recall that the conditional probability of event, say B given event, say A, P(B|A) is given by


Given the table
                                           Male      Female       Total
Income over $75,000          585          485          1,070
Income below $75,000        65            65            130
Total                                    650          550          1,200

P(being female | the person earns over $75,000) = P(Females that earns over $75,000) divided by P(people that earns over $75,000).

P(Females that earns over $75,000) =

P(people that earns over $75,000) =

Thus, P(being female | the person earns over $75,000) =

P(being female) =

Therefore, since P(being female | the person earns over $75,000) is not equal to P(being female), then "being female" and "earning over $75,000" are NOT independent events.

Therefore, the correct answer is
No, P(being female | the person earns over $75,000) ≠ P(being female)