Unit3MGMT601NOTES

docx

School

Colorado Technical University *

*We aren’t endorsed by this school

Course

ECONOMETRI

Subject

Economics

Date

Jan 9, 2024

Type

docx

Pages

Uploaded by yoknowant

Based upon the input from Units 1 and 2, you have just received your next assignment that will contribute to your next decision. For the outdoor sporting goods client, based upon your prior decision on whether or not to expand to the next market or retain your current position, justify your decision further utilizing the chi-square distribution tool . One key criterion point: You do not have adequate data to formulate a full chi-square for the outdoor sporting goods client . However, you have sufficient data to initiate this process. You are charged to demonstrate the initial steps of a nonparametric test that are qualitative. Utilizing the null and alternative hypotheses, further present your justifications for your selection and what it means beyond the mere formulas. What is this going to tell the Board of Directors and contribute to the decision-making process? The following information may be helpful in understanding chi-square and hypothesis testing: Please review this helpful video . The presenter uses flipping a coin and rolling a die. These are examples and analogies used in the CTU resources. The following are assumptions that might make the assignment more helpful and make the responses more uniform:  Continue to utilize the Big D scenario. Work under the assumption that the sample is based upon 2 different proposed product lines.  Additionally, work under the assumption that the same demographics are utilized for each product. Accept or Reject Hypothesis The purpose is to accept or reject the null hypothesis. Exceed or not exceed the critical value. Two Out comes as a result. Average Age is 24 Subtract 2-1 There is something besides chance causing more heads than tails. When calculating chi square, if the resault is a number greater than 3.841 subtract 1 If you exceed the number 3.841 you reject the hypthosis because there is something greater than chance causing heads or tails. If If you do exceed your result than you accept the “null Hypothesis” Teacher Note: “The Critical Value you must accept using a chart it is a arbitrary value found in a chart that you are supposed to be using. Go to your text book to find the definitive response for the assignment.” Dr. Wanda

Critical Value Slide: -Select 1 because there is no 0 due to having nothing to compare on outcome to -Select .05, the critical value always used in the class. -Increase to higher critical value if you want to increase certainty . The Calculated value is lower than Chi-Square. A.: Accept Teacher wants to see the calculation We need to pick two distinct products to sell. We will be using hypothetical numbers (not based on market assumptions) You can use our own numbers or research market trends.

E= Expected: 50 heads and 50 tails on 100 flips O= Observed: Example 62 heads and 38 tails on 100 flips (We are trying to find if there are observed differences between the Expected and the Observed If the “null Hypothesis” is accepted should Big D expand our not? - Yes, Expand, however we are focusing on a risk to expanding. Finding Sum Step 1

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

Finding sum Step 2 Finding sum =

More products = more steps Finding Corraltion to determine figures. Find four pairs of correlations Find ordinal correlations to a chart like the one in the assignment. Final answer: The Chi-square distribution tool can assess the decision of expanding to a new market by comparing observed data with expected data. It uses the data on consumer preferences for two proposed product lines to ascertain if there's a significant difference. The outcome of this test informs the Board of Directors' decision-making process by providing them with data-driven insight into consumer preferences. Explanation: for this direct question.

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

To evaluate our decision of whether to expand our outdoor sporting goods client's market or maintain its current position, we can utilize the preliminary data we have to initiate a Chi-square distribution test. The Chi-square distribution tool is a nonparametric method used to compare observed data with expected data to decide if a significant difference exists. Given our scenario, let's assume that our null hypothesis (H0) states that there's no difference in consumer preferences between the two proposed product lines. Our alternative hypothesis (H1), in contrast, posits that there's a significant variation in consumer preferences between these two lines. For example, suppose we gathered data from consumers about their preferences for the two proposed product lines. We would expect equal preference if H0 is correct. However, if our observed data, when compared to the expected data, yields a Chi-square test result that is statistically significant, this would suggest a strong likelihood that H1 is accurate and the preferences are not equal. The Board of Directors can utilize these findings in their decision-making process, as it adds substantiated data to the discussion. If the tests lead to rejection of the null hypothesis, this indicates clear consumer preference for one product line over the other, and the Board may be swayed to expand the market focusing on the preferred product line. Ultimately, our use of the Chi-square distribution tool makes our decision more reliable and fact-based rather than being purely speculative. The level of inventory should be 30 or greater. Sample and Population is indicated. What is the population of the zip code? What are the Demographics of the population? Discuss what the demographic is in the assignment. Control: Compare 150 nike shares & 150 Adidas Shoes Ink Equation Observed: Using the critical values chart

Learn more about Chi-square distribution here: brainly.com/question/34574271 The chi-square distribution is a probability distribution that is used to test the independence of categorical variables and to analyze the goodness-of-fit of observed data to expected values. It is characterized by a single parameter called degrees of freedom. The chi- square distribution is typically used in hypothesis testing. In this context, the test statistic follows a chi-square distribution under the null hypothesis. The test compares the observed frequencies in different categories with the expected frequencies to determine if there is a significant difference. To calculate the chi-square test statistic, you first need to define the null hypothesis and alternative hypothesis. Then, you compare the observed frequencies with the expected frequencies. The test statistic is calculated by summing the squared differences between the observed and expected frequencies, divided by the expected frequencies. The degrees of freedom for the chi-square distribution is equal to the number of categories minus 1. As the degrees of freedom increase, the chi-square distribution becomes more symmetrical. For example, let's say you want to test if there is a relationship between gender and political affiliation. You collect data from a sample of 500 individuals and record their gender (male or female) and political affiliation (Republican, Democrat, or Independent). You observe the following frequencies: - Male Republicans: 100 - Male Democrats: 80 - Male Independents: 40 - Female Republicans: 60 - Female Democrats: 100 - Female Independents: 120 To test if there is a significant relationship between gender and political

affiliation, you would calculate the expected frequencies based on the assumption of independence. For instance, the expected frequency for male Republicans can be calculated by multiplying the proportion of males in the sample (200/500) by the proportion of Republicans in the sample (160/500), which results in an expected frequency of 64. Once you have the observed and expected frequencies, you can calculate the chi-square test statistic. In this case, the degrees of freedom would be (2 - 1) * (3 - 1) = 2. If the calculated chi-square test statistic exceeds a critical value from the chi- square distribution table, you can reject the null hypothesis and conclude that there is a significant relationship between gender and political affiliation. In conclusion, the chi-square distribution is a probability distribution used in hypothesis testing to analyze the independence of categorical variables and the goodness-of-fit of observed data to expected values. It involves comparing observed and expected frequencies and calculating the chi-square test statistic. The degrees of freedom determine the shape of the distribution. By understanding the chi-square distribution and its applications, you can effectively analyze categorical data and draw meaningful conclusions. To Know More about frequency visit: brainly.com/question/33515650 #SPJ11

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

Unit3MGMT601NOTES

Related Documents