One-step inequalities: word problems

Your Solution:\newlineTo create a frequency distribution, relative frequencies, and cumulative relative frequencies, we first need to determine the range of the data and then create appropriate class intervals. After that, we can count the number of observations within each interval to find the frequency, calculate the relative frequency for each class by dividing the frequency by the total number of observations, and then calculate the cumulative relative frequency by adding the relative frequencies from the first interval to the current interval.\newlineFirst, let's find the range of the data:\newline Range = Maximum value  Minimum value  \text { Range }=\text { Maximum value }- \text { Minimum value } \newlineNext, we will decide on the number of classes and the class width. The choice of number of classes can vary, but a common rule of thumb is to use the Sturges' formula:\newlinek=1+3.322log(n) k=1+3.322 \log (n) \newlinewhere n n is the number of observations.\newlineLet's calculate the range, the number of classes, and the class width:\newline Range =16822=146k1+3.322log(150)8 \begin{array}{l} \text { Range }=168-22=146 \\ k \approx 1+3.322 \log (150) \approx 8 \end{array} \newlineWe'11l choose 88 classes for simplicity. Now, let's calculate the class width:\newline Class width = Range k=146818.25 \text { Class width }=\frac{\text { Range }}{k}=\frac{146}{8} \approx 18.25 \newlineWe can round the class width up to a convenient number, such as 2020 . Now we can create the class intervals and count the frequencies:\newline\begin{tabular}{|c|c|c|c|}\newline\hline Class Interval & Frequency (fi) \left(f_{i}\right) & Relative Frequency (rfi) \left(r f_{i}\right) & Cumulative Relative Frequency (crfi) \left(c r f_{i}\right) \\\newline\hline 2039 20-39 & f1 f_{1} & rf1=f1150 r f_{1}=\frac{f_{1}}{150} & crf1=rf1 c r f_{1}=r f_{1} \\\newline4059 40-59 & f2 f_{2} & (fi) \left(f_{i}\right) 00 & (fi) \left(f_{i}\right) 11 \\\newline(fi) \left(f_{i}\right) 22 & (fi) \left(f_{i}\right) 33 & (fi) \left(f_{i}\right) 44 & (fi) \left(f_{i}\right) 55 \\\newline(fi) \left(f_{i}\right) 66 & (fi) \left(f_{i}\right) 77 & (fi) \left(f_{i}\right) 88 & (fi) \left(f_{i}\right) 99 \\\newline(rfi) \left(r f_{i}\right) 00 & (rfi) \left(r f_{i}\right) 11 & (rfi) \left(r f_{i}\right) 22 & (rfi) \left(r f_{i}\right) 33 \\\newline(rfi) \left(r f_{i}\right) 44 & (rfi) \left(r f_{i}\right) 55 & (rfi) \left(r f_{i}\right) 66 & (rfi) \left(r f_{i}\right) 77 \\\newline(rfi) \left(r f_{i}\right) 88 & (rfi) \left(r f_{i}\right) 99 & (crfi) \left(c r f_{i}\right) 00 & (crfi) \left(c r f_{i}\right) 11 \\\newline(crfi) \left(c r f_{i}\right) 22 & (crfi) \left(c r f_{i}\right) 33 & (crfi) \left(c r f_{i}\right) 44 & (crfi) \left(c r f_{i}\right) 55 \\\newline\hline\newline\end{tabular}\newlineThe frequencies (crfi) \left(c r f_{i}\right) 66 would be counted from the list of data values for each class interval. After calculating the relative frequencies (crfi) \left(c r f_{i}\right) 77 and cumulative relative frequencies (crfi) \left(c r f_{i}\right) 88, you would plot these values to construct the histogram and frequency polygon.\newlinePlease note that due to the limitations of this format, I cannot count the individual data points and compute the frequencies, relative frequencies, and cumulative relative frequencies for you. However, the above table provides the structure to do so. Once you have the frequencies, you can simply plug in the values to calculate the relative frequencies and cumulative relative frequencies. To construct the histogram and frequency polygon, you would plot the frequencies and connect the midpoints of the top of each bar with straight lines, respectively.\newlineSolved by math-gpt.org
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33. Marks will be lost for resembling/copied work.\newline44. Put names of the group members on the cover page. Only the Group Leader to email a single copy of the work to linusaloo8888@gmail.com.\newlineASSIGNMENT I\newline11a) Briefly discuss the Discrete Fourier Transform (DFT) and derive its pair back and forth defining equations.\newlineb) Perform the circular and linear convolution of the following sequences using the DFT techniques.\newlineX1(n)={1,3,1,4}X2(n)={1,4,2,3} \begin{array}{l} X_{1}(n)=\{1,3,1,4\} \\ X_{2}(n)=\{1,4,2,3\} \\ \end{array} \newline22. An analogue filter has the transfer function, given by:\newlineT(s)=12( s+2)(s+1)(s+2) \mathrm{T}(\mathrm{s})=\frac{12(\mathrm{~s}+2)}{(\mathrm{s}+1)(\mathrm{s}+2)} \newlineConvert this to its discrete equivalent by using the impulse-invariant transform. The sampling frequency is 15 Hz 15 \mathrm{~Hz} .\newline33. Given a second-order transfer function H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} . Perform the filter realizations and write the difference equations using the cascade form via the firstorder sections.\newline44. Find the convolution of the following two sequences:\newlinex(n)={1n=0,1,20 otherwise  and h(n)={0n=01n=1,20 otherwise  x(n)=\left\{\begin{array}{ll} 1 & n=0,1,2 \\ 0 & \text { otherwise } \end{array} \text { and } h(n)=\left\{\begin{array}{ll} 0 & n=0 \\ 1 & n=1,2 \\ 0 & \text { otherwise } \end{array}\right.\right. \newlinei. Using the direct evaluation method\newlineii. Using tabular and graphical methods.\newline55 a) Describe the steps of designing digital filters.\newlineb) Given the Fourier transform of sequences {x(n)} \{x(n)\} and {h(n)} \{h(n)\} are {x(ejω)} \left\{x\left(e^{j \omega}\right)\right\} and, {H(ejω)} \left\{H\left(e^{j \omega}\right)\right\} respectively, derive the Fourier transform of:\newlinei. the delayed sequence {xk(n)} \left\{x_{k}(n)\right\} in terms of {x(ejω)} \left\{x\left(e^{j \omega}\right)\right\} , where xk(n)=x(nk) x_{k}(n)=x(n-k) \newlineii. the sequence {y(n)} \{y(n)\} in terms of H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 00 and H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 11 where H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 22\newline11\newlineASSIGNMENT II\newline11. A linear shift invariant system is described by the difference equation\newliney(n)34y(n1)+18y(n2)=x(n)+x(n1) y(n)-\frac{3}{4} y(n-1)+\frac{1}{8} y(n-2)=x(n)+x(n-1) \newlinewith H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 33 and H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 44.\newlineFind\newlinei. the natural response of the system\newlineii. the forced response of the system for a step input and\newlineiii. the frequency response of the system.\newline22. Compute the H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 55-point DFT of H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 66.\newline33. Given a sequence H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 77 for H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 88, where H(z)=0.5(1z2)1+1.3z1+0.3z2 H(z)=\frac{0.5\left(1-z^{-2}\right)}{1+1.3 z^{-1}+0.3 z^{-2}} 99, and {x(n)} \{x(n)\} 00, Evaluate its DFT X(k).\newline44. Find the digital network in direct and transposed form for the system described by the difference equation.\newliney(n)=2x(n)+0.3x(n1)+0.5x(n2)0.7y(n1)0.9y(n2) y(n)=2 x(n)+0.3 x(n-1)+0.5 x(n-2)-0.7 y(n-1)-0.9 y(n-2) \newline55. Consider the sequence {x(n)} \{x(n)\} 11. Calculate the Fast Fourier Transform (FFT).\newlineEND
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