# Forecasting Forecasting is important relative to capacity requirements planning. What are some of the merits of using judgment methods (i.e., qualitative data) in contrast to quantitative forecasting methods. Which methods are considered to be superior or more accurate, and in what forecast situations would require judgment methods? In what situations would require a quantitative approach to forecasting?

Question
Forecasting
Forecasting is important relative to capacity requirements planning.
What are some of the merits of using judgment methods (i.e., qualitative data) in contrast to quantitative forecasting methods.
Which methods are considered to be superior or more accurate, and in what forecast situations would require judgment methods?
In what situations would require a quantitative approach to forecasting?

2021-02-01
Step 1
Qualitative data forecasting techniques mainly describes the characteristics and qualities of the data. The main source of collecting the data is through feedback, interviews, questionnaire, and observations. Qualitative techniques refer to the processes which are used to make predictions about the future and do require expert judgment instead of numerical methods. Qualitative forecasting technique is based on the opinions and ideas of highly qualified and experienced professionals to forecast future results.
Step 2
Quantitative data is used when the researcher has to struggle with the quantity problem. Quantitative data are countable in nature and can be measured through scale and other instruments. Statistical Package for Social Science (SPSS), statistical analysis software is used to analyze the quantitative data.
The merits of Qualitative data over the Quantitative data will be analyzed through the following points.
Enriching
It became easier to find issues in data using the qualitative data approach rather than a quantitative approach.
Examining
Data and information generated from qualitative research can be tested using the quantitative approach.
Explaining
Qualitative data is more efficient and reliable to better understand the unpredictable results from the quantitative data as compared to the quantitative forecasting techniques.
Apart from the above merits, other merits of the qualitative forecasting techniques over quantitative techniques are, organizations can easily understand the customer’s buying behavior, customer demand, and other useful information, which is mandatory in capacity requirement planning, and that will be capable enough to fulfill the user’s requirements.
Step 3
Quantitative forecasting techniques are more accurate and superior in nature because organizations need to estimate their business activities in numbers so that the management teams can discuss the strategies, plans, and policies with the top-level management in the form of numbers. Quantitative forecasting techniques will provide the numerical form to analyze the data.
A qualitative approach is most favorable in the circumstances where it is suspected that the future outcomes will depart distinctly from the outcome in the past period, and which cannot be predicted by using the Quantitative approach. When data is unavailable, and if the data is available but not relevant then in this situation the qualitative forecasting method is used.
Quantitative techniques are the statistical techniques that required mathematical calculations to make future predictions. This method is applied when,
Numerical data of the past is available.
The assumptions that some aspects of the past will use in the future are made.

### Relevant Questions

We will now add support for register-memory ALU operations to the classic five-stage RISC pipeline. To offset this increase in complexity, all memory addressing will be restricted to register indirect (i.e., all addresses are simply a value held in a register; no offset or displacement may be added to the register value). For example, the register-memory instruction add x4, x5, (x1) means add the contents of register x5 to the contents of the memory location with address equal to the value in register x1 and put the sum in register x4. Register-register ALU operations are unchanged. The following items apply to the integer RISC pipeline:
a. List a rearranged order of the five traditional stages of the RISC pipeline that will support register-memory operations implemented exclusively by register indirect addressing.
b. Describe what new forwarding paths are needed for the rearranged pipeline by stating the source, destination, and information transferred on each needed new path.
c. For the reordered stages of the RISC pipeline, what new data hazards are created by this addressing mode? Give an instruction sequence illustrating each new hazard.
d. List all of the ways that the RISC pipeline with register-memory ALU operations can have a different instruction count for a given program than the original RISC pipeline. Give a pair of specific instruction sequences, one for the original pipeline and one for the rearranged pipeline, to illustrate each way.
Hint for (d): Give a pair of instruction sequences where the RISC pipeline has “more” instructions than the reg-mem architecture. Also give a pair of instruction sequences where the RISC pipeline has “fewer” instructions than the reg-mem architecture.
The manager at Publix recently received information that customer satisfaction dropped at noon due to overcrowding in the checkout aisle. As a result, the manager went to the main floor to record the number of customers waiting in aisles 1-10 at noon.
Which of the following choices would be an accurate description of the way the "number of customers" is used in this data set?
a. individuals for the data set
b. continuous qualitative variable for this data set
c. discrete qualitative variable for this data set
d. qualitative variable for this set
e. continuous quantitative variable for this data set
f. discrete quantitative variable for this data set
A boy is to sell lemonade to make some money to afford some holiday shopping. The capacity of the lemonade bucket is 1. At the start of each day, the amount of lemonade in the bucket is a random variable X, from which a random variable Y is sold during the day. The two random variables X and Y are jointly uniform.
What is the probability that the amount of lemonade sold is less than $$\frac{1}{3}$$?

A random sample of $$n_1 = 14$$ winter days in Denver gave a sample mean pollution index $$x_1 = 43$$.
Previous studies show that $$\sigma_1 = 19$$.
For Englewood (a suburb of Denver), a random sample of $$n_2 = 12$$ winter days gave a sample mean pollution index of $$x_2 = 37$$.
Previous studies show that $$\sigma_2 = 13$$.
Assume the pollution index is normally distributed in both Englewood and Denver.
(a) State the null and alternate hypotheses.
$$H_0:\mu_1=\mu_2.\mu_1>\mu_2$$
$$H_0:\mu_1<\mu_2.\mu_1=\mu_2$$
$$H_0:\mu_1=\mu_2.\mu_1<\mu_2$$
$$H_0:\mu_1=\mu_2.\mu_1\neq\mu_2$$
(b) What sampling distribution will you use? What assumptions are you making? NKS The Student's t. We assume that both population distributions are approximately normal with known standard deviations.
The standard normal. We assume that both population distributions are approximately normal with unknown standard deviations.
The standard normal. We assume that both population distributions are approximately normal with known standard deviations.
The Student's t. We assume that both population distributions are approximately normal with unknown standard deviations.
(c) What is the value of the sample test statistic? Compute the corresponding z or t value as appropriate.
(Test the difference $$\mu_1 - \mu_2$$. Round your answer to two decimal places.) NKS (d) Find (or estimate) the P-value. (Round your answer to four decimal places.)
(e) Based on your answers in parts (i)−(iii), will you reject or fail to reject the null hypothesis? Are the data statistically significant at level \alpha?
At the $$\alpha = 0.01$$ level, we fail to reject the null hypothesis and conclude the data are not statistically significant.
At the $$\alpha = 0.01$$ level, we reject the null hypothesis and conclude the data are statistically significant.
At the $$\alpha = 0.01$$ level, we fail to reject the null hypothesis and conclude the data are statistically significant.
At the $$\alpha = 0.01$$ level, we reject the null hypothesis and conclude the data are not statistically significant.
(f) Interpret your conclusion in the context of the application.
Reject the null hypothesis, there is insufficient evidence that there is a difference in mean pollution index for Englewood and Denver.
Reject the null hypothesis, there is sufficient evidence that there is a difference in mean pollution index for Englewood and Denver.
Fail to reject the null hypothesis, there is insufficient evidence that there is a difference in mean pollution index for Englewood and Denver.
Fail to reject the null hypothesis, there is sufficient evidence that there is a difference in mean pollution index for Englewood and Denver. (g) Find a 99% confidence interval for
$$\mu_1 - \mu_2$$.
lower limit
upper limit
(h) Explain the meaning of the confidence interval in the context of the problem.
Because the interval contains only positive numbers, this indicates that at the 99% confidence level, the mean population pollution index for Englewood is greater than that of Denver.
Because the interval contains both positive and negative numbers, this indicates that at the 99% confidence level, we can not say that the mean population pollution index for Englewood is different than that of Denver.
Because the interval contains both positive and negative numbers, this indicates that at the 99% confidence level, the mean population pollution index for Englewood is greater than that of Denver.
Because the interval contains only negative numbers, this indicates that at the 99% confidence level, the mean population pollution index for Englewood is less than that of Denver.
A boy is to sell lemonade to make some money to afford some holiday shopping. The capacity of the lemonade bucket is 1. At the start of each day, the amount of lemonade in the bucket is a random variable X, from which a random variable Y is sold during the day. The two random variables X and Y are jointly uniform.
Find and sketch the CDF and the pdf of 'Z' which is the amount of lemonade remaining at the end of the day. Clearly indicate the range of Z
A boy is to sell lemonade to make some money to afford some holiday shopping. The capacity of the lemonade bucket is 1. At the start of each day, the amount of lemonade in the bucket is a random variable X, from which a random variable Y is sold during the day. The two random variables X and Y are jointly uniform.
Write down the joint pdf of X and Y and clearly indicate the region of interest.
The bulk density of soil is defined as the mass of dry solidsper unit bulk volume. A high bulk density implies a compact soilwith few pores. Bulk density is an important factor in influencing root development, seedling emergence, and aeration. Let X denotethe bulk density of Pima clay loam. Studies show that X is normally distributed with $$\displaystyle\mu={1.5}$$ and $$\displaystyle\sigma={0.2}\frac{{g}}{{c}}{m}^{{3}}$$.
(b) Find the probability that arandomly selected sample of Pima clay loam will have bulk densityless than $$\displaystyle{0.9}\frac{{g}}{{c}}{m}^{{3}}$$.
(c) Would you be surprised if a randomly selected sample of this type of soil has a bulkdensity in excess of $$\displaystyle{2.0}\frac{{g}}{{c}}{m}^{{3}}$$? Explain, based on theprobability of this occurring.
The student engineer of a campus radio station wishes to verify the effectivencess of the lightning rod on the antenna mast. The unknown resistance $$\displaystyle{R}_{{x}}$$ is between points C and E. Point E is a "true ground", but is inaccessible for direct measurement because the stratum in which it is located is several meters below Earth's surface. Two identical rods are driven into the ground at A and B, introducing an unknown resistance $$\displaystyle{R}_{{y}}$$. The procedure for finding the unknown resistance $$\displaystyle{R}_{{x}}$$ is as follows. Measure resistance $$\displaystyle{R}_{{1}}$$ between points A and B. Then connect A and B with a heavy conducting wire and measure resistance $$\displaystyle{R}_{{2}}$$ between points A and C.Derive a formula for $$\displaystyle{R}_{{x}}$$ in terms of the observable resistances $$\displaystyle{R}_{{1}}$$ and $$\displaystyle{R}_{{2}}$$. A satisfactory ground resistance would be $$\displaystyle{R}_{{x}}{<}{2.0}$$ Ohms. Is the grounding of the station adequate if measurments give $$\displaystyle{R}_{{1}}={13}{O}{h}{m}{s}$$ and R_2=6.0 Ohms?