Randomly selected students were given five seconds to estimate the value of a product of numbers with the results shown below.
Estimates from students given 1×2×3×4×5×6×7×81×2×3×4×5×6×7×8:

169, 500, 5635, 10000, 45000, 50, 5000, 800, 1000, 200169, 500, 5635, 10000, 45000, 50, 5000, 800, 1000, 200

Estimates from students given 8×7×6×5×4×3×2×18×7×6×5×4×3×2×1:

400, 40320, 500, 350, 450, 225, 1500, 428, 550, 40000400, 40320, 500, 350, 450, 225, 1500, 428, 550, 40000

Use a 0.050.05 significance level to test ?0:?21=?22H0:σ12=σ22 vs. ??:?21≠?22Ha:σ12≠σ22 :

(a) The test statistic is

(b) The larger critical value is

(c) The conclusion is
A. There is not sufficient evidence to reject the claim that the two populations have equal variances. (So, we can assume the variances are equal.)
B. There is sufficient evidence to reject of the claim that the two populations have equal variances. (So, we can assume the variances are unequal.)

3. a) Using only the following information:   

• ∆H°f for NO (g) is +90.4 kJ/mol
   • ∆H° = –56.6 kJ/mol for the reaction: NO (g) + 1/2 O2 (g) à  NO2 (g)  

Determine ∆H°f for NO2 (g).

b) Using only your answer to (a) and the following information:    

•∆H° = –283.0 kJ/mol for the reaction: CO (g) + 1/2 O2 (g) à  CO2 (g)  Determine ∆H° for the reaction:   4 CO (g) + 2 NO2 (g) à  4 CO2 (g) + N2 (g)

c) A 10.0-L vessel contains 5.0 atm of CO and 3.0 atm of NO2 at 25°C. How much heat (in Joules) will be liberated if this is allowed to react to completion according to the reaction in part (b)?
d) In a separate experiment using a very large reaction vessel with a movable piston, 6.00 moles of CO2 (g) reacts completely with 3.00 moles of nitrogen gas according to the following equation at 25°C and with

a constant external pressure of 2.00 atm:

4 CO2 (g) + N2 (g) à  4 CO (g) + 2 NO2 (g)     
  This reaction proceeds to completion. Calculate ∆U, q, and w for this reaction under these conditions.

1. Create the probability distribution in a table for all the outcomes where X is the random variable representing the number of points awarded. (already done)

2. Communicate how you arrived at the probability of each outcome.

3. What is the expected value, E(X), for the game? You may include this in your table from the distribution. If the game costs 10 points to play, how much would the player expect to win or lose?

Three Prize roller

Word scramble

a)

Ten spinner

How do I calculate the inicial concentration of^​​ I^- and S2O8^2- in each mixture, the reaction rate M/s, and the k value (rate constant) from the following data???? IODINE CLOCK REACTION

Run#1-time was 41.45 sec   Run#2-time was 120.48 sec   Run#3-231.64 sec   Run#4-36.88 sec    Run#5-231.70 sec

I need this answered not using excel

Given the following data, construct a material requirements plan which will result in 100 units of parent #1 (P1), at the beginning of week 6 and 200 units of parent #2 (P2) at the beginning of week 8:

In this lab, you will implement Heap Sort algorithm in C++ and Report the number of steps and the CPU running time in a table,

Approximation the constant c in the complexity of heap sort (cnlgn) by inspecting the results

For each algorithm, and for each n = 100, 200, 300, 400, 500, 1000, 4000, 10000, measure its running time and number of steps when the input is (1) already sort, i.e. n, n-1, …, 3, 2,1; (2) reversely sorted 1, 2, 3, … n; (3) random permutation of 1, 2, …, n; (4) 50 instances of n random numbers generated in the range of [1..n].

1.Develop a multiple linear regression model to predict the price of a house using the square feet of living area, number of bedrooms, and number of bathrooms as the predictor variables

1.     Write the reqression equation.
2.      Discuss the statistical significance of the model as a whole using the appropriate regression statistic at a 95% level of confidence.
3. Discuss the statistical significance of the coefficient for each independent variable using the appropriate regression statistics at a 95% level of confidence.
4. Interpret the coefficient for each independent variable.
5.   What percentage of the observed variation in housing prices is explained by the model?
6. Determine the prediction interval of a house with 3,000 square feet of living area, 3 bedrooms, and 2.5 bathrooms, and comment on the prediction interval.

   Prepare a single Microsoft Excel file to document your regression analyses. Prepare a single Microsoft Word document that outlines your responses for each portion of the case study.

   Selling Price        Living Area (Sq Feet)      No. Bathrooms No Bedrooms    Age (Years)

   $240,000              2,022     2.5          3              20

   $235,000              1,578     2              3              20

   $500,075              3,400     3              3              20

   $240,000              1,744     2.5          3              20

   $270,000              2,560     2.5          3              20

   $225,000              1,398     2.5          3              20

   $280,000              2,494     2.5          3              20

   $225,000              2,208     2.5          4              20

   $248,220              2,550     2.5          3              20

   $275,000              1,812     2.5          2              20

   $137,000              1,290     1              2              20

   $150,000              1,172     2              2              20

   $649,000              4,128     3.5          3              20

   $195,000              1,816     2.5          3              97

   $373,200              2,628     2.5          4              20

   $169,450              1,254     2.5          3              20

   $144,200              1,660     1.5          4              20

   $189,900              1,850     1.5          3              20

   $166,000              1,258     2              3              20

   $160,000              1,219     2              3              20

   $327,355              1,850     2.5          3              20

   $247,000              2,103     2.5          3              20

   $318,000              1,806     2.5          3              20

   $341,000              1,674     1.5          2              17

   $288,650              2,242     2.5          3              20

   $157,000              1,408     1.5          3              20

   $449,000              3,457     2.5          3              21

   $142,000              1,728     1.5          3              21

   $389,000              2,354     2.5          3              21

   $476,000              2,246     2.5          3              21

   $249,230              1,902     2.5          2              21

   $139,900              1,178     1              3              21

   $301,900              2,896     3.5          4              21

   $425,000              2,457     3              3              41

   $121,000              936         1              3              50

   $150,000              934         1              2              21

   $138,000              1,279     1              3              21

   $199,900              1,888     2              3              26

   $145,000              1,686     1.5          4              21

   $465,000              2,310     3              2              21

   $158,000              1,200     1.5          3              21

Many regions in North and South Carolina and Georgia have experienced rapid population growth over the last 10 years. It is expected that the growth will continue over the next 10 years. This has motivated many of the large grocery store chains to build new stores in the region. The Kelley’s Super Grocery Stores Inc. chain is no exception. The director of planning for Kelley’s Super Grocery Stores wants to study adding more stores in this region. He believes there are two main factors that indicate the amount families spend on groceries. The first is their income and the other is the number of people in the family. Food and income are reported in thousands of dollars per year, and the variable size refers to the number of people in the household.

   a) Develop a correlation matrix. Do you see any problems with multicollinearity?  

   b) Determine the regression equation. Discuss the regression equation. How much does an additional family member add to the amount spent on food?  

     c) What is the value of R2? Can we conclude the model is significant?  

     d) Would you consider deleting either of the independent variables?  

     e) Plot the residuals in a histogram. Is there any problem with the normality assumption?

     f) Plot the fitted values against the residuals. Does this plot indicate any problems with homoscedasticity?

Many regions in North and South Carolina and Georgia have experienced rapid population growth over the last 10 years. It is expected that the growth will continue over the next 10 years. This has motivated many of the large grocery store chains to build new stores in the region. The Kelley’s Super Grocery Stores Inc. chain is no exception. The director of planning for Kelley’s Super Grocery Stores wants to study adding more stores in this region. He believes there are two main factors that indicate the amount families spend on groceries. The first is their income and the other is the number of people in the family. The director gathered the sample information and it is in the file Kelley’s Super Grocery. Food and income are reported in thousands of dollars per year, and the variable size refers to the number of people in the household.

   a) Develop a correlation matrix. Do you see any problems with multicollinearity?  

   b) Determine the regression equation. Discuss the regression equation. How much does an additional family member add to the amount spent on food?

     c) What is the value of R2? Can we conclude the model is significant?  

     d) Would you consider deleting either of the independent variables?  

     e) Plot the residuals in a histogram. Is there any problem with the normality assumption?

     f) Plot the fitted values against the residuals. Does this plot indicate any problems with homoscedasticity?

Many regions in North and South Carolina and Georgia have experienced rapid population growth over the last 10 years. It is expected that the growth will continue over the next 10 years. This has motivated many of the large grocery store chains to build new stores in the region. The Kelley’s Super Grocery Stores Inc. chain is no exception. The director of planning for Kelley’s Super Grocery Stores wants to study adding more stores in this region. He believes there are two main factors that indicate the amount families spend on groceries. The first is their income and the other is the number of people in the family. Food and income are reported in thousands of dollars per year, and the variable size refers to the number of people in the household.

   a) Develop a correlation matrix. Do you see any problems with multicollinearity?  

   b) Determine the regression equation. Discuss the regression equation. How much does an additional family member add to the amount spent on food?  

     c) What is the value of R2? Can we conclude the model is significant?  

     d) Would you consider deleting either of the independent variables?  

     e) Plot the residuals in a histogram. Is there any problem with the normality assumption?

     f) Plot the fitted values against the residuals. Does this plot indicate any problems with homoscedasticity?