Please use matlab language

You are provided with a modified file provided by Our World in Data that contains COVID?19 data. The file is named owid?covid?data.xlsx. It contains 43824 rows and 42 columns of data. You cannot modify any contents of the file.

Open the file and familiarise yourself with the headers. Some of the key headers include:

? Location: The location/country

? Continent: The continent of the location

? Days_tracked: The days since COVID?19 was first tracked in the location

? Total_cases: The total cases of COVID?19

? New_cases: The new daily cases of COVID?19

? Total_deaths: The total deaths due to COVID?19

? New_deaths: The new daily deaths due to COVID?19

Source: https://ourworldindata.org/covid?cases

Q1a

In the Q1a.m file, use importdata() to import the contents of owid?covid?data.xlsx. It is important to check what fields the imported data structure contains.

Use input() to prompt the user for a location. In figure(1)1, make a 2?by?2 subplot and plot the following with a '??.' (dotted?double?dash) line specification. Turn on the grid and provide a title that includes the location for all panels.

? [top?left panel] Total cases against days tracked

? [top?right panel] Total deaths against days tracked

? [bottom?left panel] New cases against days tracked

? [bottom?right panel] New deaths against days tracked

The code should continue to prompt the user if they would like to repeat the same task with another location. 1

Data for another country should overwrite figure(1) . An example output of the process is provided below.

. Consider a zero-mean WSS complex Gauss-Markov process of order 1 defined by the following equation r =-ar _tv, n=0,1,.... where v ~ /(0, o') and Ela, v* ] = 0 for 1 = +1, 12, .... Multiply both sides by * and take expectation values to find Er, *]. Note that E[rv*] = Ex*v,]. Multiply both sides by r* and take expectation values to show R., [0] = -aR_ [-1] + 0) = -aR* [1]+02. This process is also known as the auto-regressive process of order 1 and is denoted by AR(1). . Now multiply both sides by e* , I = 1, 2...., and take expec- tation values to show R, [!] = -aR,, [[ - 1], 1 =1, 2. .... This result, for a Gauss-Markov process of order P, or an AR(P) process. forms the basis for high resolution spectral estimation of zero-mean WSS random signals.Consider a Galton-Watson process (Xn)n where we assume that initially, there is exactly one ancestor, i.e. X0 = 1. Assume that the probability for each individual in each generation to have exactly j descendants is given by (3-1) pj = 19(1 p)j, where 0 0) of the species. 0 Find the expected number ,u of descendants of each individual. 0 Determine no for each possible value of p. Consider the following Markov chain with the following transition diagram on states {1, 2, 3} al- 2 CO 173 3 (a) Is this Markov chain irreducible? [1 marks] (b) Find the probability of the Markov chain to move to state 3 after two time steps, providing it starts in state 2. [3 marks]1. Each box of a particular brand of cereals contains a plastic figure. There are four types of figures, each equally likely. Let T denote the number of boxes you need to buy until you have all four kinds of figures. Determine the PGF Gr(s) and P(T = k) for each k. 2. X has the Poisson distribution with parameter Y, where Y is itself random. Namely, Y Po(u). Show that Gx+Y(s) = explu(sex-1 -1)]. 3. Consider a Galton-Watson process with offspring distribution geometric from zero (P(X = k) = (1 -p)*p.) Let 7 := min {t : Z, =0} if this minimum exists, and 7 =co otherwise. Determine P(T = (). 4. Consider a Galton-Watson process with offspring distribution X " Bi(2, p). (i) Determine the extinction probability q explicitly; (ii) Determine Var(Z, ). (iii) Show that when p = ; then P(Z > 0) ~ 8/1. (Here ~ means the ratio tends to one.)