What are the five major divisions of the brain and their associated psychological functions?

     The five major divisions of the brain are the telencephalon, the diencephalon, the mesencephalon, the metencephalon, and the myelencephalon. The telencephalon, which is the human brain's largest division, is responsible for mediating the most complex functions of the brain (Pinel, 2009). It is responsible for initiating voluntary movement, interprets sensory input, and mediates complex cognitive processes such as speaking, problem solving, and learning (Pinel, 2009). The diencephalon is a divison of the human brain, which is composed of the thalamus and the hypothalamus. The thalamus has sensory relay nuclei, which receive signals from sensory receptors, then processes the signals, and transmits those signals to the designated areas of the sensory cortex (Pinel, 2009). The hypothalamus plays a role in regulating several motivated behaviors by regulating the release of hormones from the pituitary gland (Pinel, 2009).

     The mesencephalon is a division that is comprised of two divisions, which are the tectum and the tegmentum. The tectum is composed of the inferior colliculi, which have an auditory function, and the superior colliculi, which have a visual function (Pinel, 2009). The tegmentum contains three structures, which are the periaqueductal gray, the substantia nigra, and the red nucleus. The periaqueductal gray has a role in mediating the analgesic (pain-reducing) effects of opiate drugs (Pinel, 2009). The substantia nigra and the red nucleus are important components of the sensorimotor system (Pinel, 2009). The metencephalon is a division that has two major divisions, which are the pons and the cerebellum. The cerebellum is a sensorimotor structure, which function is sensorimotor control. The myelencephalon, also referred to as the medulla, is the most posterior division of the brain (Pinel, 2009). It plays a role in arousal and is  is responsible for functions such as sleep, movement, attention, the maintenance of muscle tone, and various cardiac, circulatory, and respiratory reflexes (Pinel, 2009).

 Reference

 Pinel, J.P.J. (2009). Biopsychology (7th ed.). Boston, MA: Allyn and Bacon.

What is the relationship between genes, cells, and behavior?

     The relationship between genes, cells, and behavior is critical to the interactions between genes and cells, which have an impact on behavior. Directly genes do not specify behavior, rather, genes encode proteins, which are unique to certain types of cells. Such as neurons, and gives the cells their character making a neuron different from other cells. Genes and cells build and govern brain functioning, which expresses behavior. Brain activity, development, and behavior depend on the interactions of genes and cells and on influences which are environmental and inherited, which impact brain gene expression and behavior (NCBI, 2011).

 Reference

 Pinel, J. P. J. (2009). Biopsychology (7th ed.). Boston, MA: Allyn and Bacon.

NCBI. (2011). Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3052688/

Individual Assignment

11. List the five steps of hypothesis testing, and explain the procedure and logic of each.

Step 1: Aron, Aron, and Coups, (2009) “restate the question as a research hypothesis and a null hypothesis about the populations” (p. 115). Here one makes a research hypothesis concerning a predicted relation among populations. The null and research hypothesizes are the opposite of each other. A correct research hypothesis means the null hypothesis cannot be correct, and a correct null hypothesis means the research hypothesis cannot be correct.

Step 2: Aron, Aron, and Coups, (2009) “determine the characteristics of the comparison distribution” (p. 115). By reaching a true null hypothesis the population situation represents the comparison distribution, which is the distribution compared to the score and based on the results of the sample.

Step 3: Aron, Aron, and Coups, (2009) “determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected” (p. 115). Here one rejects the null hypothesis if the point of the cutoff sample score reaches or exceeds the sample score. If the null hypothesis is true the Z score is set at a score, which would be unlikely.

Step 4: Aron, Aron, and Coups, (2009) “determine your sample’s score on the comparison distribution” (p. 115). Here one gathers the test’s sample results.

Step 5: Aron, Aron, and Coups, (2009) “decide whether to reject the null hypothesis” (p. 115). Here one either declares the test invalid or rejects the null hypothesis by comparing the cut off Z score to the sample’s Z score.

14. Based on the information given for each of the following studies, decide whether to reject the null hypothesis. For each, give (a) the Z-score cutoff (or cutoffs) on the comparison distribution at which the null hypothesis should be rejected, (b) the Z score on the comparison distribution for the sample score, and (c) your conclusion. Assume that all populations are normally distributed.

Population

Study              µ          σ         Sample score           p                Tails of Test

A                                 5          1                 7                   .05                1 (high predicted)

B                                 5          1                 7                   .05                2

C                                 5          1                 7                   .01                1 (high predicted)

D                                 5          1                 7                   .01                2

A) (a) 1.645 Z score cutoff, (b) Z = 2 (c) reject the null hypothesis

B) (a) 1.96 Z score cutoff,  (b) Z = 2, (c) reject the null hypothesis,

C) (a) 2.3263 Z score cutoff, (b) Z = 2, (c) fail to reject the null hypothesis,

D) (a) 2.576 Z score cutoff, (b) Z = 2 (c) fail to reject the null hypothesis,

18. A researcher predicts that listening to music while solving math problems will make a particular brain area more active. To test this, a research participant has her brain scanned while listening to music and solving math problems, and the brain area of interest has a percentage signal change of 58. From many previous studies with this same math problems procedure (but not listening to music), it is known that the signal change in this brain area is normally distributed with a mean of 35 and a standard deviation of 10. (a) Using the .01 level, what should the researcher conclude? Solve this problem explicitly using all five steps of hypothesis testing, and illustrate your answer with a sketch showing the comparison distribution, the cutoff (or cutoffs), and the score of the sample on this distribution. (b) Then explain your answer to someone who has never had a course in statistics (but who is familiar with mean, standard deviation, and Z scores).

Population

Study             µ                      σ          Sample Score             p                      Tails of Test

A                     100.0               10.0                 80                    .05                   1 (low predicted)

B                     100.0               20.0                 80                    .01                   2

C                     74.3                 11.8                 80                    .01                   2

D                     16.9                 1.2                   80                    .05                   1 (low predicted)

E                      88.1                 12.7                 80                    .05                   2

(A)  The researcher should conclude whether there is or is not sufficient statistical evidence that music increases the math problem solving skills.  

Step 1: Aron, Aron, and Coups, (2009) “restate the question as a research hypothesis and a null hypothesis about the populations” (p. 115).

Does listening to music while solving math problems make a particular brain area more active?

Population 1: Music increases the math problem solving skills.

Population 2: Music has no effect on math problem solving skills.

Step 2: Aron, Aron, and Coups, (2009) “determine the characteristics of the comparison distribution” (p. 115).

It is assumed that music increases the math problem solving skills. The null hypothesis is “Music has no effect on math problem solving skills.” The comparison distribution is population two’s distribution.  

Step 3: Aron, Aron, and Coups, (2009) “determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected” (p. 115).

Reject the null hypothesis if the music has no effect on math problem solving skills score is within the bottom or the top 2.5% of the comparison distribution. The cutoff Z scores for the 1% level are -2.33 or 2.33.     

Step 4: Aron, Aron, and Coups, (2009) “determine your sample’s score on the comparison distribution” (p. 115).

Z = (x - m)/s = (58 - 35)/10 = 2.30      

Step 5: Aron, Aron, and Coups, (2009) “decide whether to reject the null hypothesis” (p. 115).

Since 2.30 < 2.3263, therefore fails to reject the null hypothesis. 

(b) Seeing that the p-value is greater than 1%, one fails to reject the null hypothesis. The result of this one test is not sufficient evidence to reject the belief that the mean percentage is 0.35.  

Reference

Aron, A., Aron, E. N., & Coups, E. (2009). Statistics for psychology (5th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

If anxiety and depression are correlated, what three possible directions of causality might explain this correlation?

     When two variables have a significant correlation one assume there is something causing them to go together. A correlation is a description of a relationship between two variables, which are either directly related to each other, or they share a common cause (Aron, Aron, & Coupe, 2009). A direction of causality is a path of causal effect, therefore X may be thought to cause Y, or Y may be thought to cause X, or that something else causes X and Y (Aron, Aron, & Coups, 2009). If anxiety and depression are correlated, there are three possible directions of causality that might explain this correlation. One causality could be that anxiety causes depression. A second causality could be that depression causes anxiety. A third causality could be that there is an environmental stimuli that causes both anxiety and depression. One may be able to rule out one or more of these three possible directions of causality based on additional knowledge of the situation (Aron, Aron, & Coups, 2009). In order to do so one must investigate the situation.  

 Reference

Aron, A., Aron, E. N., & Coups, E. (2009). Statistics for psychology (5th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

If the correlation between age and physical flexibility is -.68, what does this mean? How would this correlation look on a scatter diagram? What general shape would it have?

     A correlation is a description of a relationship between two variables (Aron, Aron, & Coupe, 2009). The relationship between two equal-interval numeric variables is described by a normal measure of a correlation (Aron, Aron, & Coupe, 2009). If indeed the correlation between age and physical flexibility is -.68, then this means that the older individual is he or she has less physical flexibility. This is considered a negative correlation. A negative correlation is a relation between two variables in which high scores on one go with low scores on the other (Aron, Aron, & Coupe, 2009). On a scatter diagram as for the horizontal axis and vertical axis, the horizontal axis represents age and the vertical axis represents physical flexibility. Therefore, with a correlation between age and physical flexibility of -.68 (negative correlation) the scatter diagram the dots would go downward starting from the left toward the right basically in a straight line. When a correlation is negative it slopes downward from left to the right basically in a straight line (Aron, Aron, & Coups, 2009). If this was a positive correlation then as for a scatter diagram the dots basically follow a straight line sloping up and from the left to the right (Aron, Aron, & Coups, 2009).

 Reference

Aron, A., Aron, E. N., & Coups, E. (2009). Statistics for psychology (5th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Hypothesis Testing

     A hypothesis is a prediction, which one expects to occur and intends to test in a research study (Aron, Aron, & Coups, 2009). Hypothesis testing is a process using statistics to determining if the results of a study support a certain theory, which one believes applies to a certain population (Aron, Aron, & Coups, 2009). Hypothesis testing is a process that involves five steps: 

Step 1: Restate the question as a research hypothesis and a null hypothesis about the populations. 

In this first step one makes a research hypothesis concerning a predicted relation among populations. The null and research hypothesizes are the opposite of each other. A correct research hypothesis means the null hypothesis cannot be correct, and a correct null hypothesis means the research hypothesis cannot be correct. 

Step 2: Determine the characteristics of the comparison distribution.

In the second step by reaching a true null hypothesis the population situation represents the comparison distribution, which is the distribution compared to the score and based on the results of the sample. 

Step 3: Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected. 

In this third step, reject the null hypothesis if the point of the cutoff sample score reaches or exceeds the sample score. If the null hypothesis is true the Z score is set at a score, which would be unlikely. 

Step 4: Determine your sample’s score on the comparison distribution. 

In this fourth step one gathers the test’s sample results. 

Step 5: Decide whether to reject the null hypothesis. 

In this fifth step one either declares the test invalid or rejects the null hypothesis by comparing the cut off Z score to the sample’s Z score.

Reference

Aron, A., Aron, E. N., & Coups, E. (2009). Statistics for psychology (5th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Individual Text Assignment

11. For the following scores, find the (a) mean, (b) median, (c) sum of squared deviations, (d) variance, and (e) standard deviation:

2, 2, 0, 5, 1, 4, 1, 3, 0, 0, 1, 4, 4, 0, 1, 4, 3, 4, 2, 1, 0

(a) mean, 42/21 = 2 (b) median, 2 (c) sum of squared deviations, 46 (d) variance, 46/21 = 2.19  and (e) standard deviation, 1.47

12. For the following scores, find the (a) mean, (b) median, (c) sum of squared deviations, (d) variance, and (e) standard deviation:

1,112; 1,245; 1,361; 1,372; 1,472

(a) mean, 6,562/5 = 1,312 (b) median, 1,361 (c) sum of squared deviations, 76,090  (d) variance, 76,090/5 = 15,218  and (e) standard deviation, 123.361

13. For the following scores, find the (a) mean, (b) median, (c) sum of squared deviations, (d) variance, and (e) standard deviation:

3.0, 3.4, 2.6, 3.3, 3.5, 3.2

(a) mean, 19/6 = 3.166 (b) median, 3.25 (c) sum of squared deviations, 0.533 (d) variance, 0.533/6 = 0.088 and (e) standard deviation 0.296

16. A psychologist interested in political behavior measured the square footage of the desks in the official office of four U.S. governors and of four chief executive officers (CEOs) of major U.S. corporations. The figures for the governors were 44, 36, 52, and 40 square feet. The figures for the CEOs were 32, 60, 48, and 36 square feet. (a) Figure the means and standard deviations for the governors and for the CEOs. (b) Explain, to a person who has never had a course in statistics, what you have done. (c) Note the ways in which the means and standard deviations differ, and speculate on the possible meaning of these differences, presuming that they are representative of U.S. governors and large corporations’ CEOs in general.

(a) Governors - mean = 43, standard deviations = 6.83; CEOs - mean = 44, standard deviations = 12.65

(b) To figure the mean add up all the scores and divide this sum by the number of scores, such as for the governors, 40 + 36 + 52 + 40 + = 172/4 the mean is 43, which is the same process for CEOs (Aron, Aron, & Coups, 2009). To figure the standard deviations figure the variance and take the square root. First figure the median, line up all the scores from lowest to highest, figure how many scores there are to the middle score by adding 1 to the number of scores and dividing by 2, and then count up to the middle score or scores, which is 42 (Aron, Aron, & Coups, 2009). Next locate the sum of squared deviation by subtracting the listed scores minus the means, and then square the result. Then add each end result and divide by the number of scores. Next find the variance by taking the SS, which is 140 and divide it by the numbers of scores, which is 4. The variance is 35. Now calculate the square root of the variance, which is the standard deviation.

(c) The mean is a measure when the distribution of data is continuous and symmetrical and it is the average. While standard deviation is the most used way of describing the spread of a group of scores and is the average amount that scores differ from the mean (Aron, Aron, & Coups, 2009). I would have to guess that individuals in a high power of authority such as CEOs and governors would have large desk which in a way represent then power they hold. With CEOs making more money and controlling powerful companies it would seem they would have larger desk.

21. Payne (2001) gave participants a computerized task in which they first see a face and then a picture of either a gun or a tool. The task was to press one button if it was a tool and a different one if it was a gun. Unknown to the participants while they were doing the study, the faces served as a “prime” (something that starts you thinking a particular way); half the time they were of a black person and half the time of a white person. Table 2–9 shows the means and standard deviations for reaction times (the time to decide if the picture is of a gun or a tool) after either a black or white prime. (In Experiment 2, participants were told to decide as fast as possible.) Explain the results to a person who has never had a course in statistics. (Be sure to explain some specific numbers as well as the general principle of the mean and standard deviation.)

The mean is the measure when the distribution of data is continuous and symmetrical, while standard deviation is the most used way of describing the spread of a group of scores (Aron, Aron, & Coups, 2009). As for the gun the means of 423 and 441 were the best measures of central tendency from experiment 1 and the standard deviations were 64 and 73, which showed just how far apart or spread they were from the mean.

14. On a standard measure of hearing ability, the mean is 300 and the standard deviation is 20. Give the Z scores for persons who score (a) 340, (b) 310, and (c) 260. Give the raw scores for persons whose Z scores on this test are (d) 2.4, (e) 1.5, (f) 0, and (g) -4.5.

(a) 340, -2 (b) 310, -0.5 (c) 260, 2 (d) 2.4, 348 (e) 1.5, 330 (f) 0, 300 and (g) -4.5, 210 

15. A person scores 81 on a test of verbal ability and 6.4 on a test of quantitative ability. For the verbal ability test, the mean for people in general is 50 and the standard deviation is 20. For the quantitative ability test, the mean for people in general is 0 and the standard deviation is 5. Which is this person’s stronger ability: verbal or quantitative? Explain your answer to a person who has never had a course in statistics.

To figure this out take the score of 81, which is 31 above the verbal ability test mean of 50, and divide by 20, which is (31/20) = 1.5. Therefore 81 is 1.5 standard deviations above the mean score for verbal ability. To figure the score of 6.4, which is 6.4 above the quantitative ability mean of 0 divide it by 5, which is 6.4/5 = 1.28 standard deviations above the mean of the quantitative ability test. Therefore with a Z score of 1.5 on verbal ability and a Z score of 2.8 on quantitative ability the person’s stronger ability is verbal ability.  

22. Suppose you want to conduct a survey of the attitude of psychology graduate students studying clinical psychology toward psychoanalytic methods of psychotherapy. One approach would be to contact every psychology graduate student you know and ask them to fill out a questionnaire about it. (a) What kind of sampling method is this? (b) What is a major limitation of this kind of approach?

(a) This would be considered nonrandom sampling. (b) This type of sampling, only gives little guarantee that the sample will be representative of the entire population. This sampling is biased because it would not take into account for the psychology graduate students that are unknown.

25. You are conducting a survey at a college with 800 students, 50 faculty members, and 150 administrators. Each of these 1,000 individuals has a single listing in the campus phone directory. Suppose you were to cut up the directory and pull out one listing at random to contact. What is the probability it would be (a) a student, (b) a faculty member, (c) an administrator, (d) a faculty member or administrator, and (e) anyone except an administrator? (f) Explain your answers to someone who has never had a course in statistics.

(a) a student, 800/1000 or 8% probability  (b) a faculty member, 50/1000 or 5% probability (c) an administrator, 150/1000 or 15% probability (d) a faculty member or administrator, 200/1000 or 20% probability (e) anyone except an administrator, 850/1000 or 85% probability (f) Probability is the measure or estimation of how likely that something will occur. To determine the probability one has to divide the number of a certain group to choose from (800 students) by the total number of the survey population (1000). Therefore, there is a 800/1000 or .08% or 8% probability.

 Reference

Aron, A., Aron, E. N., & Coups, E. (2009). Statistics for psychology (5th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Individual Text Assignment

12. Explain and give an example for each of the following types of variables: (a) equal-interval, (b) rank-order, (c) nominal, (d) ratio scale, (e) continuous.

(a) An equal-interval variable is variable by which numbers represent numbers stand for almost exact equal amounts of what is being measured (Aron, Aron, & Coups, 2009). An example is the difference between stress ratings of 2 and 4 means about as much as the difference between 5 and 7. (b) A rank-order or ordinal variables is a variable by which numbers stand for relative ranking only (Aron, Aron, & Coups, 2009). An example is a car models’ standing in a safety class ranking. (c) Nominal variable is a variable by which the values are categories or names (Aron, Aron, & Coups, 2009). An example is the nominal variable student; the values are traditional and nontraditional. (d) A ratio scale is a scale of measurement of data, which allows comparisons of the differences of values. An example is the time measured from the "Big Bang" until present is on a ratio scale, because before the “Big Bang” time had not begun on Earth. (e) Aron, Aron, and Coups (2009), “with a continuous variable, there are in theory an infinite number of values between any two values” (p. 4). An example is measuring height because the variables would be continuous. There are an unlimited number of possibilities of height even when only looking at between 4 and 5.2 feet.

15. Following are the speeds of 40 cars clocked by radar on a particular road in an 35-mph zone on a particular afternoon:

30, 36, 42, 36, 30, 52, 36, 34, 36, 33, 30, 32, 35, 32, 37, 34, 36, 31, 35, 20,

24, 46, 23, 31, 32, 45, 34, 37, 28, 40, 34, 38, 40, 52, 31, 33, 15, 27, 36, 40

Make (a) a frequency table and (b) a histogram. Then (c) describe the general shape of the distribution.

(a)    Frequency Table

SPEED	FREQUENCY	PERCENTAGE
15-19	1	2.5
20-24	3	7.5
25-29	2	5
30-34	15	37.5
35-39	11	27.5
40-44	4	10
45-49	2	5
50-54	2	5

(b) Histogram

(c) The general shape of distribution is unimodal.

19. Give an example of something having these distribution shapes: (a) bimodal, (b) approximately rectangular, and (c) positively skewed. Do not use an example given in this book or in class.

(a) Bimodal: an example is a day’s account of new drivers taken the written examination driver test. The majority of participants scored between 85-98%, the second largest category of participants scored between 84-88%, and the remainder of participants scored inconsistently between 55% and 99%.  

(b) Approximately rectangular: an example is an online college classroom of 25 traditional and nontraditional students. 15 of the students were 19 years of age and 10 were 32 years of age, which generates a rectangular distribution.

 (c) Positively skewed: an example is a case study of 25 college seniors, whereas one computes the hours of study spent on coursework daily, which may show positively skewed distribution. In this case study 10 students spent 2-3 hours studying daily, 11 spent 3 hours studying daily, and 3 students spent 4-5 hours studying daily. Giving outcomes positively skewed.   

20. Find an example in a newspaper or magazine of a graph that misleads by failing to use equal interval sizes or by exaggerating proportions.

This graph shows the stock market plummeted the day after President Barack Obama’s re-election but it does not show the trend of losses before the President’s re-election. The plummet started on May, 2008, which is not indicated. This leads individuals to believe the drop resulted from President Barack Obama’s re-election.

21. Nownes (2000) surveyed representatives of interest groups who were registered as lobbyists of three U.S. state legislatures. One of the issues he studied was whether interest groups are in competition with each other. Table 1–10 shows the results for one such question. (a) Using this table as an example, explain the idea of a frequency table to a person who has never had a course in statistics. (b) Explain the general meaning of the pattern of results.

(a) Frequency tables are used to explain data gathered and are a way to display certain factors present. These tables are used to find the mean of a large set of data values. In table 1-10, what is demonstrated is what the specific group encounters competition. 20% experiences no competition, 58% experiences some competition, and 22% experiences a lot of competition. (b) The general meaning of the pattern of results from table 1-10, shows results split up exhibiting a specific frequency of a group which encounters rivalry from similar groups. All responses are represented in percentage and number patterns, which indicate the relationship occurring between the groups.    

22. Mouradian (2001) surveyed college students selected from a screening session to include two groups: (a) “Perpetrators”—students who reported at least one violent act (hitting, shoving, etc.) against their partner in their current or most recent relationship—and (b) “Comparisons”—students who did not report any such uses of violence in any of their last three relationships. At the actual testing session, the students first read a description of an aggressive behavior such as, “Throw something at his or her partner” or “Say something to upset his or her partner.” They then were asked to write “as many examples of circumstances of situations as [they could] in which a person might engage in behaviors or acts of this sort with or towards their significant other.” Table 1–11 shows the “Dominant Category of Explanation” (the category a participant used most) for females and males, broken down by comparisons and perpetrators. (a) Using this table as an example, explain the idea of a frequency table to a person who has never had a course in statistics. (b) Explain the general meaning of the pattern of results.

(a) The information in the frequency table explains by sorting the data briefly and clearly. The table exhibits frequency and the percentage of occurrences team members, male and female experienced in each category situation.

(b) The general meaning of the results shows the trend of outcomes for the table, whereas the majority of women perpetrators (27%) display intimate aggression because of control motives, and the majority of men perpetrators (31%) display expressive aggression. The combined majority of intimate aggression of men and women was rejection of perpetrator or act with 46%, and the combined lowest of intimate aggression of men and women was prosocial/acceptable explanations with 0%.

Reference

Aron, A., Aron, E. N., & Coups, E. (2009). Statistics for psychology (5th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Clark, P. (2012). The New York Observer. Retrieved from http://observer.com/2012/11/stocks-fall-on-day-after-obama-reelection-but-not-as-far-as-in-2008/