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MAC1105 Chapter 1: Art Across Cultures and Time Relationships between Art, Religion, and Knowledge in Renaissance and Beyond

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aishamukhtar707
23 Feb 2023
School
Miami Dade College
Department
Mathematics: Calculus & Pre-Calculus
Course
MAC1105
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Document Summary

Art across cultures and time: relationships between art, religion, and. The relationship between art and religion is complex and varied, and it can differ significantly based on the country or culture of origin. Art has often been used as a means to express and illustrate religious beliefs, stories, and values. For instance, the art of the christian renaissance often depicted religious figures, biblical scenes, and religious themes in paintings, sculptures, and architecture. In contrast, islamic art traditionally avoids the representation of living creatures and focuses on geometric patterns and calligraphy, which serve as visual representations of the. Other cultures, such as those with animistic beliefs, may incorporate the use of masks and totems in their religious ceremonies and rituals. The renaissance was a period of great innovation and creativity, during which there was a renewed interest in art, science, philosophy, and math. There are many connections between these subjects, as they are all fundamental to human knowledge and understanding.

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Related Questions

***Please see the attachment for complete details***
Global Health and Global Wealth
This project gives you the opportunity to use statistics to investigate the relationship between Global Health and Global Wealth. Although, anecdotally, wealthier countries are expected to have healthier populations, there is significant variability surrounding that relationship. Attached are some data for you to use to investigate the relationship for yourself. Within the data you will find 22 randomly selected countries from around the world. For each country you will find a variety of economic and healthcare indicators (see the data dictionary for a definition of each variable). Truthfully, there is not one single factor that explains overall health in a selected location. In fact, we would expect many different variables to contribute to the general health of a population. However, for this assignment, you are to determine the indicator that you believe best predicts general health, as measured by life expectancy. You must use the data given to you.
1. Investigation Results - Using the given data, investigate the possible relationships between Life Expectancy as the response variable $(y)$ and each of the three explanatory variables (x). For each x variable, you will complete the following steps. (Note: you will do parts a -d three times!) (60 points)
a. Construct a scatter diagram displaying the relationship between x and y.
You can use graph paper and draw the diagram by hand, use your calculator and take a picture of the screen, or use the online site: https://www. desmos.com/, which will allow you to print or save your diagram. Whatever tool you use, be sure to choose an appropriate scale for the axes so that the relationship between the variables is easy to see.
b. Calculate and state the sample correlation coefficient r.
c. Describe the type of correlation, if any, and interpret the correlation in the context of the data.
d. Determine if the correlation is significant. Use and show all steps of this process.
 
2. Inferences - Write at least one paragraph for each of the following questions. In the paragraph, you should explain as though you are talking to someone that is not in a statistics class. In other words, give details. A paragraph is 3-5 well-developed sentences. (40 points)
a. Now that you have investigated the relationships between y and each of the three different x variables, which explanatory variable (x) is the best predictor for Life Expectancy (y)? To defend your choice, discuss your investigation results for each (x, y) pairing from part 1 , including correlation coefficients and their significance.
b. Calculate the regression equation for the relationship you determined to be the "best" in part a. What is the "rate of change" of your equation? Using this rate of change, describe the behavior of Life Expectancy (y) as a result of changes in the explanatory variable (x) that you chose.
c. Discuss the overall fitness of your regression line to the data set, by graphing the line on your scatter plot and by considering the correlation coefficient. Would you say that the explanatory variable you chose is reasonably predictive of Life Expectancy? Why or why not?
d. You may have noticed that the United States was not included in the data set you were given. Below are the relevant statistics for the United States.

Analyze and write about the results of a visual and an auditory lexical decision task. Analyze a large data set that includes students’ responses for both the visual and auditory modality. Lab is a write-up of these findings.

  1. One large data file that includes all experimental trial responses for both the Visual and Auditory modality tasks. Note that the sample size for the visual experiment is 16 and for the auditory experiment is 15.

Presentedz with visual words and pseudo-words in one experiment and auditory words and pseudo-words in a second experiment. Respond whether you saw/heard a real word of English or not. In the visual task, remained fixated on a cross (i.e., ‘+’) presented in the centre of the screen, while the stimulus was visually presented either to the left or right of the fixation point. In the auditory experiment, you heard words and pseudo-words presented either to your left or right ear.

  Words Pseudo-words Number 60 60 Pronounceable N/A Yes Hemi-field/Ear Presentation 30 left/30 right 30 left/30 right String Length

Range: 5-7

Mean: 6.01 (SD = 0.71)

Range: 5-7

Mean: 5.85 (SD = 0.78)

Phoneme Length

Range: 5-7

Mean: 5.45 (SD = 0.59)

Range: 3-6

Mean: 4.58 (SD = 0.87)

Number of Morphemes 1 N/A

In each experiment, there were 60 words and 60 pseudo-words. It was the same 120 items presented in each experiment. Only their modality of presentation changed. Thirty words and 30 pseudo-words were presented to the left (side of the screen in the visual experiment, ear in the auditory experiment), while the other 30 words and other 30 pseudo-words are presented to the right. Side of presentation was balanced across participants using two lists. Each list contained the same set of words and pseudo-words; only presentation side was counter-balanced across lists.

Independent samples t-tests revealed no difference in orthographic length between the words and pseudo-words (t(117) = -1.59, p = 0.11); there is, however, a reliable phoneme length difference between the words and pseudo-words (t(104.28) = -6.37, p < 0.001). We also recorded whether the participant was a native speaker of English or not and whether they are right- or left-hand dominant. Feel free to use these factors in your analysis.

 

  1. Given what you know about the organization of the visual and auditory pathways and lateralization of language processing, state, in very clear terms, what your predictions are. Provide specific predictions for your observation (dependent) variable(s), and select and name your predictor (independent) variable(s). 
  2.  
  3. Provide a detailed list of the processing steps in R that is performed to arrive at your results. For example, do you want to include incorrect trials trials in your analysis of both dependent variables? Do not provide the R code, but instead write out these steps in plain English.  
  4. Provide a series of plots that provide an illustration of your results. You should minimally include a plot of the accuracy and reaction time results and this should be done for each modality. You may also included histograms of your reaction time distributions, but this is not necessary. Be sure your axes are appropriately labeled. 
  5. Provide a table that presents your numerical findings in a clear manner. Remember to include both the sample-level averages and standard deviations per condition. 
  6. Discuss your results in light of the predictions in Q1 and your findings in Q3 and Q4. Make specific reference to your predictions and the extent to which they are borne out. 
  7. Get creative: Incorporate one other factor (e.g., native language, handedness). State your predictions and provide a breakdown of the data in terms of these factors. 
  8. Design your own research question: Consider how you might use the same experimental design to understand another linguistic phenomenon and population (e.g. stop VOT, vowel length, lexical tone, Mandarin speakers, French speakers etc.). State your research question, and provide and motivate specific predictions for your dependent variable(s) as a function of your predictor variable(s). Note: Ideally, the new research question will still involve language lateralization. Consult the Gazzaniga readings online for ideas based on the particular specializations of each hemisphere. 

8. Write a class called WordSet representing a set of String objects which can contain an arbitrary number of strings, limited only by the memory available to the Java Virtual Machine. A set is a collection of elements, however, unlike a list, a set cannot contain duplicate elements. Therefore, as its name implies, a WordSet object cannot contain duplicate Strings that is, if one attempts to da String to a Wordset, and the wordset already contains an element which is equal to this string, the attempt will fail and the state of the Wordset will not change. All String comparisons performed in the methods defined in the Wordset class are done in a Case SENSITIVE manner. Note that in the method descriptions below, the phrase "this Wordset" means "the Wordset on which the method in question is called." Your Wordset class MUST provide the following INSTANCE methods • A constructor, which takes no parameters and initializes the new Wordset ohject so that it contains no elements • A method called add(), which takes as its only parameter a string and returns a value of type boolean. If this Wordset already contains a string which is equal to the parameter string, or the parameter String is null, then the state of this Wordset does not change and the method return false; otherwise, the parameter String is added to this Wordset. and the method returns true. • A method called remove().which takes as its only parameter a string and returns a value of type boolean. If this wordSet contains a string which is equal to the parameter String this string is removed from the WordSet and the method returns true. On the other hand, if the string parameter is null or this Wordset does not contain a string which is equal to the parameter string, then the state of this wordset does not change, and the method return false. • A method called get.size(), which takes no parameters and returns the number of strings currently stored in this Wordset. This method MUST NOT change the state of this Wordset. • A method called isMember(). which takes as its only parameter a string and retumsa value of type boolean which is true if this wordset contains the parameter String false otherwise. If the parameter String is null, this method also return false. This method MUST NOT change the state of this wordset. • A method called computebirrerence().which takes as its only parameter a Wordset and returns a new Wordset representing the difference between this wordset and the parameter Wordset: in other words, the WordSet returned by this method contains all the strings that are in this wordset, but not in the parameter Wordset. If the parameter Wordset contains all the elements of this WordSet or this WordSet contains no elements, then this method returns a new Wordset containing no elements. Finally, if the parameter Wordset is null or contains ne strings, then this method returns a new wordset which contains all the elements of this wordset. This method MUST NOT change the state of this wordset or the parameter Wordset. • A method called tostring , which takes the parameters and turns a string which is the textual representation of this wordset. This textual representation consists of the concatena tion of the following clements - The String - The text representation of each clement in the WordSet; cach pair of adjacent clements is separated by the String", but this String MUST NOT appear before the first clement or after the last element - The String") The order in which the elements of this Wordset appear in the textual representation generated by the tostring() method does not matter. If the WordSet contains to Brings, then the textual representation returned by this method is ". Note that you MUST respect proper encapsulation practices that is, the attributes and methods of your class MUST be declared using the proper visibility modifier NINT Um an array list (of string) to keep track of the string stored in a wordt ob joot Is there a method defined in the Array loist class which determines whether in clementis already wored in an array ist, and which will do a case-sensitive comparison when liked on an Arraylint of strings? See the pages 24-26 of this examination for information about potentially useful methods defined by the ArrayList class WRITE YOUR Wordset CLASS IN THE SPACE BELOW: