Children of three ages are asked to indicate their preference for three photographs of
adults. Do the data suggest that there is a significant relationship between age and
photograph preference? What is wrong with this study? [Chi-Square = 29.6, with 4
df: ? < 0.05].

The development of accounting information systems is much more than the software for ledger posting and report formation. It also involves establishing procedures for capturing data and distribution, as well as analysis of accounting information. In an accounting information system, there are three basic entities that need to be considered when specifying a system, namely, transactions, account and processing period. Outline the relationship between these three entities.

(Outline a range of considerations for developing accounting system specifications).

Many organizations use information technology vendors to develop company solutions. Determine at least three (3) challenges associated with using vendors. Analyze the relationship between competitive advantage and vendor relationship management overall.

Specify at least three (3) approaches for marketing IT’s value. Propose (1) method for implementing each approach within an organization. Provide one (1) example of each approach to support your answer.

Month of April

Required:

1. Record the transaction for April in general journal.

2. Open general ledger accounts, using the T-accounts provided, and post the general journal entries to the ledger.

Month of May

Required:

1. Record the transactions for May in general journal.

2. Post the transactions into T-accounts created for the month of April.

An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use α = 0.05.

Find the value of the test statistic for method of loading and unloading.

_____________.

Find the p-value for method of loading and unloading. (Round your answer to three decimal places.)

p-value = _________.

Find the value of the test statistic for type of ride.

____________.

Find the p-value for type of ride. (Round your answer to three decimal places.)

p-value = __________.

Find the value of the test statistic for interaction between method of loading and unloading and type of ride.

____________.

Find the p-value for interaction between method of loading and unloading and type of ride. (Round your answer to three decimal places.)

p-value = _____________.

An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use α = 0.05.

a) Find the value of the test statistic for method of loading and unloading.

Find the p-value for method of loading and unloading. (Round your answer to three decimal places.)

p-value =

b) Find the value of the test statistic for type of ride.

Find the p-value for type of ride. (Round your answer to three decimal places.)

p-value =

c) Find the value of the test statistic for interaction between method of loading and unloading and type of ride.

Find the p-value for interaction between method of loading and unloading and type of ride. (Round your answer to three decimal places.)

p-value =

Please help me with activity 8, answer of 6 and 7 are below it

Activity 8: If you add the proportions of variability in taste that can explained by each variable individually (your results from Activity 6), you do not get the same result as the proportion of variability that can be explained by the combined model in Activity 7. Why is this? Look at the relationships that the predictor variables have with one another by constructing scatterplots and finding the correlations between hydrogen sulfide and lactic acid, between hydrogen sulfide and acetic acid, and between lactic acid and acetic acid.

Activity 6

What proportion of the variability in taste can be explained by hydrogen sulfide?

r^2 =0.7558*0.7558=0.5712

What proportion of the variability in taste can be explained by lactic acid?

r^2 =0.7042*0.7042=0.4959

What proportion of the variability in taste can be explained by acetic acid?

r^2 =0.5495*0.5495=0.3020

Activity 7

Estimate the equation of the regression line predicting taste score based on all three predictor variables in a single equation.

taste = -28.877 + 0.328 x Acetic +3.912 x H2S + 19.671 x Lactic

What taste score would you predict for a cheese whose hydrogen sulfide measurement was 5.0, whose acetic acid measurement was 6.1, and whose lactic acid measurement was 0.90?

taste = 10.39

What proportion of the variability in taste can be explained by the model using all three predictor variables?

R^2 = 0.6518

In many agricultural and biological experiments, one may use a two‑way model with only one observation per cell. When one of the factors is related to the grouping of experimental units into more uniform groups, the design may be called a randomized complete block design (RCBD). The analysis is similar to a two‑way analysis of variance (question B) except that the model does not include an interaction term.

            The specific leaf areas (area per unit mass) of three types of citrus each treated with one of three levels of shading are stored in Table C. The first column contains the code for the shading treatment, the second column contains the code for the citrus species, and the third column contains the specific leaf area. Assume that there is no interaction between citrus species and shading. Carry out a two‑way analysis of this data.

            The shading treatment and citrus species are coded as follows:

            Treatment        Code                Species                        Code

            Full sun           1                      Shamouti orange         1

            Half shade       2                      Marsh grapefruit          2

            Full shade        3                      Clementine mandarin 3

nCopy the treatment code, the species code, and the specific leaf area into the EXCEL worksheet, label the columns and look at the data.

                                                                                                                                       {Example 1}

nPerform a two‑way (without interaction) analysis of this data and answer the following questions. Use a 5% significance level.

{Example 26}

            Recall that the confidence interval for a difference between two means is based on a calculation of the margin of error of the estimated difference. With a common variance (Error MS) and the same number of observations in all shading treatments, the margin of error of an estimated difference will be the same whether we calculate it for treatments 1 and 2, 1 and 3, or 2 and 3. This margin of error of the difference between two means is sometimes referred as the least significant difference (LSD).

nCalculate the LSD for comparing shading treatments in this experiment.

LSD = critical tvalue ´standard error of difference.

Use the critical t value with 4 degrees of freedom is t _0.025,4= 2.776.

n is the number of times of times each treatment was tested (in this case n = 3 for the 3 species).

what are the ethical responsilities of a firm to its employees and customers.

can selling and distribution expenses vary by customers & why